DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on XXXXXXXXXXXXXX has been entered.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
Claims X are canceled.
Claims X are amended.
Claims X are new.
Claims X are pending and have been examined.
This action is in reply to the papers filed on XXX (effective filing date xxx).
Claims 1-20 are pending and have been examined.
This action is in reply to the papers filed on 10/09/2024 (effective filing date 10/09/2023).
Information Disclosure Statement
No Information Disclosure Statement has been filed.
The information disclosure statement(s) submitted: xxxxxxxx, has/have been considered by the Examiner and made of record in the application file.
Amendment
The present Office Action is based upon the original patent application filed on xxx as modified by the amendment filed on xxx.
Reasons For Allowance
Prior-Art Rejection withdrawn
Claims xxx are allowed. The closest prior art (See PTO-892, Notice of References Cited) does not teach the claimed:
The invention teaches… and the prior-art teaches…, however, the prior-art does not teach…
The closest prior-art (xxx) teach the features as disclosed in Non-final Rejection (xxxx), however, these cited references do not teach and the prior-art does not teach at least the following combination of features and/or elements:
determining, at a second time after associating the information corresponding to the first loyalty card with the logged location, that a second user computing device is located within a specified distance of the logged location using a second positioning system of the second user computing device; in response to determining that the second user computing device is located within the specified distance of the logged location of the first user computing device at the first time of detecting: retrieving information corresponding to a second loyalty card, the second loyalty card being associated with the merchant and the second user computing device; and displaying, by the second user computing device, data describing the second loyalty card.
Claim Rejections - 35 USC §101 - Withdrawn
Per Applicant’s amendments and arguments and considering new guidance in the MPEP, the rejections are withdrawn. Specifically, in Applicant’s Remarks (dated 03/14/2017, pgs. 8-11), Applicant traverses the 35 USC §101 rejections arguing that the amended claims recite new limitations that are not abstract, amount to significantly more, are directed to a practical application, etc… For example, Applicant argues….
In support of their arguments, Applicant cites to the following recent Fed. Cir. court cases (i.e., Alice Corp. v. CLS Bank Int’l, SRI Int’l, Inc. v. Cisco Systems, Inc., Ultramercial, Inc. v. Hulu, LLC, Berkheimer, Core Wireless, McRO, Enfish, Bascom, DDR, etc…).
Claim Rejections - 35 USC § 101
35 U.S.C. § 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter because the claimed invention is directed to an abstract idea without significantly more. These claims recite a method, system, and computer readable medium for increasing query-answering agent accuracy.
Claim 11 recites [a] computer-implemented method comprising: responsive to receiving a query related to an industrial unit and using at least one processor, generating a consultation prompt based on the query; retrieving, using a consultation agent, a response to the query; generating, based on the response, an evaluation prompt; retrieving, using an evaluation agent, an evaluation of the response; based on determining that the evaluation of the response is positive, generating a summarization prompt based on the response; retrieving, using a summarization agent, a response summary; and storing the response summary in a response set used to generate an answer comprising a repair plan, the answer to be transmitted to a scheduling system for scheduling repairs to the industrial unit.
The claims are being rejected according to the 2019 Revised Patent Subject Matter Eligibility Guidance (Federal Register, Vol. 84, No. 5, p. 50-57 (Jan. 7, 2019)).
Step 1: Does the Claim Fall within a Statutory Category?
Yes. Claims 11-19 recite a method and, therefore, are directed to the statutory class of a process. Claims 1-10 recite a system/apparatus and, therefore, are directed to the statutory class of machine. Claim 20 recites a non-transitory computer readable medium/computer product and, therefore, are directed to the statutory class of a manufacture.
Step 2A, Prong One: Is a Judicial Exception Recited?
Yes. The following tables identify the specific limitations that recite an abstract idea. The column that identifies the additional elements will be relevant to the analysis in step 2A, prong two, and step 2B.
Claim 11: Identification of Abstract Idea and Additional Elements, using Broadest Reasonable Interpretation
Claim Limitation
Abstract Idea
Additional Element
11. A computer-implemented method comprising:
No additional elements are positively claimed.
responsive to receiving a query related to an industrial unit and using at least one processor, generating a consultation prompt based on the query;
This limitation includes the step(s) of: responsive to receiving a query related to an industrial unit and using at least one processor, generating a consultation prompt based on the query.
But for the processor, this limitation is directed to processing and/or communicating known information (e.g., receiving a query) to facilitate increasing query-answering agent accuracy which may be categorized as any of the following:
mental process – concepts performed in the human mind (including an observation, evaluation, judgment, opinion)
and/or
certain method of organizing human activity –
fundamental economic principles or practices (including hedging, insurance, mitigating risk), and/or
commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations), and/or
managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions).
using at least one processor, generating a consultation prompt
retrieving, using a consultation agent, a response to the query;
This limitation includes the step(s) of: retrieving, using a consultation agent, a response to the query.
No additional elements are positively claimed.
This limitation is directed to processing and/or communicating known information (e.g., retrieving a response) to facilitate increasing query-answering agent accuracy which may be categorized as any of the following:
mental process – concepts performed in the human mind (including an observation, evaluation, judgment, opinion)
and/or
certain method of organizing human activity –
fundamental economic principles or practices (including hedging, insurance, mitigating risk), and/or
commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations), and/or
managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions).
No additional elements are positively claimed.
generating, based on the response, an evaluation prompt;
This limitation includes the step(s) of: generating, based on the response, an evaluation prompt.
No additional elements are positively claimed.
This limitation is directed to processing and/or communicating known information to facilitate increasing query-answering agent accuracy which may be categorized as any of the following:
mental process – concepts performed in the human mind (including an observation, evaluation, judgment, opinion)
and/or
certain method of organizing human activity –
fundamental economic principles or practices (including hedging, insurance, mitigating risk), and/or
commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations), and/or
managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions).
No additional elements are positively claimed.
retrieving, using an evaluation agent, an evaluation of the response;
This limitation includes the step(s) of: retrieving, using an evaluation agent, an evaluation of the response.
No additional elements are positively claimed.
This limitation is directed to processing and/or communicating known information to facilitate increasing query-answering agent accuracy which may be categorized as any of the following:
mental process – concepts performed in the human mind (including an observation, evaluation, judgment, opinion)
and/or
certain method of organizing human activity –
fundamental economic principles or practices (including hedging, insurance, mitigating risk), and/or
commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations), and/or
managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions).
No additional elements are positively claimed.
based on determining that the evaluation of the response is positive, generating a summarization prompt based on the response;
This limitation includes the step(s) of: based on determining that the evaluation of the response is positive, generating a summarization prompt based on the response.
No additional elements are positively claimed.
This limitation is directed to processing and/or communicating known information to facilitate increasing query-answering agent accuracy which may be categorized as any of the following:
mental process – concepts performed in the human mind (including an observation, evaluation, judgment, opinion)
and/or
certain method of organizing human activity –
fundamental economic principles or practices (including hedging, insurance, mitigating risk), and/or
commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations), and/or
managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions).
No additional elements are positively claimed.
retrieving, using a summarization agent, a response summary; and
This limitation includes the step(s) of: retrieving, using a summarization agent, a response summary.
No additional elements are positively claimed.
This limitation is directed to processing and/or communicating known information to facilitate increasing query-answering agent accuracy which may be categorized as any of the following:
mental process – concepts performed in the human mind (including an observation, evaluation, judgment, opinion)
and/or
certain method of organizing human activity –
fundamental economic principles or practices (including hedging, insurance, mitigating risk), and/or
commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations), and/or
managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions).
No additional elements are positively claimed.
storing the response summary in a response set used to generate an answer comprising a repair plan, the answer to be transmitted to a scheduling system for scheduling repairs to the industrial unit.
This limitation includes the step(s) of: storing the response summary in a response set used to generate an answer comprising a repair plan, the answer to be transmitted to a scheduling system for scheduling repairs to the industrial unit.
No additional elements are positively claimed.
This limitation is directed to processing and/or communicating known information to facilitate increasing query-answering agent accuracy which may be categorized as any of the following:
mental process – concepts performed in the human mind (including an observation, evaluation, judgment, opinion)
and/or
certain method of organizing human activity –
fundamental economic principles or practices (including hedging, insurance, mitigating risk), and/or
commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations), and/or
managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions).
No additional elements are positively claimed.
As shown above, under Step 2A, Prong One, the claims recite a judicial exception (an abstract idea). The claims are directed to the abstract idea of increasing query-answering agent accuracy, which, pursuant to MPEP 2106.04, is aptly categorized as a mental process and/or a method of organizing human activity. Therefore, under Step 2A, Prong One, the claims recite a judicial exception.
Next, the aforementioned claims recite additional functional elements that are associated with the judicial exception, including: processor for communicating information and memory for storing instructions. Examiner understands these limitations to be insignificant extrasolution activity. (See Accenture, 728 F.3d 1336, 108 U.S.P.Q.2d 1173 (Fed. Cir. 2013), citing Cf. Diamond v. Diehr, 450 U.S. 175, 191-192 (1981) ("[I]nsignificant post-solution activity will not transform an unpatentable principle in to a patentable process.”).
The aforementioned claims also recite additional technical elements including: a “processor” and “memory” for implementing the system and a “non-transitory computer-readable storage medium” for storing executable instructions. These limitations are recited at a high level of generality and appear to be nothing more than generic computer components. Claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 134 S. Ct. at 2358, 110 USPQ2d at 1983. See also 134 S. Ct. at 2389, 110 USPQ2d at 1984.
Step 2A, Prong Two: Is the Abstract Idea Integrated into a Practical Application?
No. The judicial exception is not integrated into a practical application. The additional elements listed above that relate to computing components are recited at a high level of generality (i.e., as generic components performing generic computer functions such as communicating, receiving, processing, analyzing, and outputting/displaying data) such that they amount to no more than mere instructions to apply the exception using generic computing components. Simply implementing the abstract idea on a generic computer is not a practical application of the abstract idea. Additionally, the claims do not purport to improve the functioning of the computer itself. There is no technological problem that the claimed invention solves. Rather, the computer system is invoked merely as a tool. Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore, these claims are directed to an abstract idea.
Furthermore, looking at the elements individually and in combination, under Step 2A, Prong Two, the claims as a whole do not integrate the judicial exception into a practical application because they fail to: improve the functioning of a computer or a technical field, apply the judicial exception in the treatment or prophylaxis of a disease, apply the judicial exception with a particular machine, effect a transformation or reduction of a particular article to a different state or thing, or apply the judicial exception beyond generally linking the use of the judicial exception to a particular technological environment. Rather, the claims merely use a computer as a tool to perform the abstract idea(s), and/or add insignificant extra-solution activity to the judicial exception, and/or generally link the use of the judicial exception to a particular technological environment.
Step 2B: Does the Claim Provide an Inventive Concept?
Next, under Step 2B, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, when considered both individually and as an ordered combination, do not amount to significantly more than the abstract idea. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. Simply put, as noted above, there is no indication that the combination of elements improves the functioning of a computer (or any other technology), and their collective functions merely provide conventional computer implementation. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements relating to computing components amount to no more than applying the exception using a generic computing components. Mere instructions to apply an exception using a generic computing component cannot provide an inventive concept. Furthermore, the broadest reasonable interpretation of the claimed computer components (i.e., additional elements) includes any generic computing components that are capable of being programmed to communicate, receive, send, process, analyze, output, or display data. Furthermore, Applicant’s Specification (PGPub. 2025/0117757 [0127]) refers to a general computer system, but they do not include any technically-specific computer algorithm or code.
Additionally, pursuant to the requirement under Berkheimer, the following citations are provided to demonstrate that the additional elements, identified as extra-solution activity, amount to activities that are well-understood, routine, and conventional. See MPEP 2106.05(d).
Capturing an image (code) with an RFID reader. Ritter, US Patent No. 7734507 (Col. 3, Lines 56-67); “RFID: Riding on the Chip” by Pat Russo. Frozen Food Age. New York: Dec. 2003, vol. 52, Issue 5; page S22.
Receiving or transmitting data over a network. Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362; OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014).
Storing and retrieving information in memory. Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93.
Outputting/Presenting data to a user. Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015); MPEP 2106.05(g)(3).
Using a machine learning model to determine user segment characteristics for an ad campaign. https://whites.agency/blog/how-to-use-machine-learning-for-customer-segmentation/.
Thus, taken alone and in combination, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea), and are ineligible under 35 USC 101.
Independent system claim 1 and CRM claim 20 also contains the identified abstract ideas, with the additional elements of a processor and storage medium, which are a generic computer components, and thus not significantly more for the same reasons and rationale above.
Dependent claims 2-10 and 12-19 further describe the abstract idea. The additional elements of the dependent claims fail to integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea. Thus, as the dependent claims remain directed to a judicial exception, and as the additional elements of the claims do not amount to significantly more, the dependent claims are not patent eligible.
As such, the claims are not patent eligible.
Invention Could be Performed Manually
It is conceivable that the invention could be performed manually without the aid of machine and/or computer. For example, Applicant claims generating a consultation, retrieving a response, generating an evaluation, etc… Each of these features could be performed manually and/or with the aid of a simple generic computer to facilitate the transmission of data.
See also Leapfrog Enterprises, Inc. v. Fisher-Price, Inc., and In re Venner, which stand for the concept that automating manual activity and/or applying modern electronics to older mechanical devices to accomplish the same result is not sufficient to distinguish over the prior art. Here, applicant is merely claiming computers to facilitate and/or automate functions which used to be commonly performed by a human.
Leapfrog Enterprises, Inc. v. Fisher-Price, Inc., 485 F.3d 1157, 82 USPQ2d 1687 (Fed. Cir. 2007) "[a]pplying modern electronics to older mechanical devices has been commonplace in recent years…"). The combination is thus the adaptation of an old idea or invention using newer technology that is commonly available and understood in the art.
In In re Venner, 262 F.2d 91, 95, 120 USPQ 193, 194 (CCPA 1958), the court held that broadly providing an automatic or mechanical means to replace manual activity which accomplished the same result is not sufficient to distinguish over the prior art. MPEP 2144.04, III Automating a Manual Activity.
MPEP 2144.04 III - Automating a Manual Activity and In re Venner, 262 F.2d 91, 95, 120 USPQ 193, 194 (CCPA 1958) further stand for and provide motivation for using technology, hardware, computer, or server to automate a manual activity.
Therefore, the Office finds no improvements to another technology or field, no improvements to the function of the computer itself, and no meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, based on the two-part Alice Corp. analysis, there are no limitations in any of the claims that transform the exception (i.e., the abstract idea) into a patent eligible application.
Claim Rejections - Not an Ordered Combination
None of the limitations, considered as an ordered combination provide eligibility, because taken as a whole, the claims simply instruct the practitioner to implement the abstract idea with routine, conventional activity.
Claim Rejections - Preemption
Allowing the claims, as presently claimed, would preempt others from increasing query-answering agent accuracy. Furthermore, the claim language only recites the abstract idea of performing this method, there are no concrete steps articulating a particular way in which this idea is being implemented or describing how it is being performed.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 11, 20 are rejected under 35 U.S.C. 103 as being unpatentable over: Deal 2014/0101079; in view of Castel et al. 2014/0164603.
18/911,074 – Claim 1. Deal 2014/0101079 teaches A system comprising: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, configure the system to perform operations comprising (Deal 2014/0101079 [0016; Claim 1]): responsive to receiving a query related to an industrial unit (Deal 2014/0101079 [0046 - information … takes the form of questions] Agent inputs consist of human and machine contributions of information items to the problem solving activity. In one embodiment, information provided by the MDPSA takes the form of questions; inputs from participating agents include answers to questions, contributions to discussions, photographs, data graphics, video representations, and audio representations. For example, the MDPSA could ask, "What expertise is needed to alleviate this situation?" Both human and machine agents would subsequently respond with their ideas in some cases supported by authoritative data sources. In one embodiment, the MDPSA executes a search of the network for information of relevance to the problem solving instance. Search findings are treated as agent inputs. They are included by reference or are archived within the MDPSA. [0055-0056 - questions]), generating a consultation prompt based on the query (Deal 2014/0101079 [0424 – prompts and wizards] Progress through the steps is facilitated by a combination of MDPSA prompts and participating agent selections as shown in FIG. 9. Facilitation is implemented as described by Warfield, Christakis, Delbecq, Van de Ven and Gustafson, and Pergamit and Peterson. Facilitation is comprised of set-up facilitation and process facilitation. In one embodiment, initiation of an instance is accomplished by means of a wizard which uses a recipe-like guide to set up of the problem-solving process. The products of the recipe are descriptions of the context of a problematic situation and the constraints which influence execution of a problem-solving process. In one embodiment, initiation of the re-planning process is accomplished with a wizard. The re-planning wizard proceeds summarily through the first six steps of the process allowing an agent re-starting an instance to assess the steps which need to be revisited. [0428 - dialogues] In one embodiment, computational linguistics and graphics-processing algorithms generate summaries of dialogues. Summary dialogues are continually updated and continuously available to support problem solving. Complete dialogues are stored in an archive for use when detailed review or processing of agent inputs is necessary.); retrieving, using a consultation agent, a response to the query (Deal 2014/0101079 [0046 - inputs from participating agents include answers to questions] Agent inputs consist of human and machine contributions of information items to the problem solving activity. In one embodiment, information provided by the MDPSA takes the form of questions; inputs from participating agents include answers to questions, contributions to discussions, photographs, data graphics, video representations, and audio representations. For example, the MDPSA could ask, "What expertise is needed to alleviate this situation?" Both human and machine agents would subsequently respond with their ideas in some cases supported by authoritative data sources. In one embodiment, the MDPSA executes a search of the network for information of relevance to the problem solving instance. Search findings are treated as agent inputs. They are included by reference or are archived within the MDPSA. [0059 - a cycle of question, answer, clarification, selection, structuring and refinement is at the core of the process. Agents respond to questions and then engage in dialogue to clarify responses and achieve a common understanding of each response] Groups of agents explore collective and contrasting perspectives and achieve consensus in accordance with facilitated dialogue methods. In one embodiment, a cycle of question, answer, clarification, selection, structuring and refinement is at the core of the process. Agents respond to questions and then engage in dialogue to clarify responses and achieve a common understanding of each response. Polling is used to select those answers that are perceived to have the greatest impact on the complex problem. Pairwise comparison is used to structure means-end relationships among clarified ideas. Agents review graphic depictions of relationships and engage in dialogues to suggest modifications that refine outputs as represented in the graphic representations.); generating, based on the response, an evaluation prompt (Deal 2014/0101079 [0436 - assessments] Scoring can be approached in a variety of ways. In one embodiment, scoring is linked to contribution statistics, qualitative attributes of interpersonal interactions, contribution effectiveness, argument errors and fallacious reasoning, and peer assessments.); retrieving, using an evaluation agent, an evaluation of the response (Deal 2014/0101079 [0051 - a five-point Likert scale could be used to score an item, or a polar assessment of `useful` or `not useful` could be assigned] Agents use metadata as a tool for identifying and retrieving information. Agent needs for metadata vary by the criteria they use to select information item. For example, a machine agent may seek to access a stored piece of information by data type or data size. Human agents may employ semantics or contextual cues as aids to associative retrieval. In one embodiment, human and machine participants and the MDPSA apply metadata to information articles for the purpose of retrieval. Examples of metadata include information-item creation name, keywords, data type, author name, thumbnail representations, creation date, agent name, contribution date and time, scoring, and number of times the information article was accessed. In one embodiment, agents assign a score to an information item to indicate its usefulness or lack of utility in supporting a problem solving activity. For example, a five-point Likert scale could be used to score an item, or a polar assessment of `useful` or `not useful` could be assigned. [0083 - peer assessments contribute positively and negatively to the expertise score] In one particular embodiment, agents receive three scores. The first score is based on their performance in a single MDPSA instance. This score drives players to excel in the extant instance. A second score is based on performance over all MDPSA instances in which an agent has participated. This score is an indicator of general problem solving skill. A third score represents an agent's expertise in a particular discipline or subject area. The third score is calculated by examining an agent's contribution in a specific expertise area, such as power generation or education, over all instances in which the agent provided expertise in that discipline. Evidence of contribution influence is also included in the expertise calculation. In one embodiment, influence is determined by natural language processing or graphical analyses that assess whether an agent's contribution served as an organizing principle around which other contributions were arranged. Expertise can also be recognized by other participants as a breakthrough. In one embodiment, peer assessments contribute positively and negatively to the expertise score.); based on determining that the evaluation of the response is positive, generating a summarization prompt based on the response (Deal 2014/0101079 [0428 - summaries of dialogues] In one embodiment, computational linguistics and graphics-processing algorithms generate summaries of dialogues. Summary dialogues are continually updated and continuously available to support problem solving. Complete dialogues are stored in an archive for use when detailed review or processing of agent inputs is necessary.); retrieving, using a summarization agent, a response summary (Deal 2014/0101079 [0428 - Summary dialogues are continually updated and continuously available to support problem solving] In one embodiment, computational linguistics and graphics-processing algorithms generate summaries of dialogues. Summary dialogues are continually updated and continuously available to support problem solving. Complete dialogues are stored in an archive for use when detailed review or processing of agent inputs is necessary.); and storing the response summary in a response set used to generate an answer comprising a repair plan, the answer to be transmitted to a scheduling system for scheduling repairs to the industrial unit (Deal 2014/0101079 [0044 - storing information items] Through a network, ubiquitous access to a problem solving instance is achieved at any time and from any location that has connectivity with a network on which the MDPSA has been implemented. Network protocols enable agents to access and to be accessed by the MDPSA for the purpose of collecting agent inputs and information items, processing information, generating outputs, and referencing and storing information items. [0050 - remote information recorded as a web site or stored in a networked database could be accessed by agents through file transfer protocols, hyperlinks or other access means] Inputs can be stored either in a central location, in multiple locations, or by reference. Information that is frequently updated by authoritative sources, such as population data, national debt figures, or salary information is stored by reference to ensure the most recent updates are available to support problem solving activities. In one embodiment, virtual references to remotely stored information items are included in the archive. For example, remote information recorded as a web site or stored in a networked database could be accessed by agents through file transfer protocols, hyperlinks or other access means. References are generated by agents and by the MDPSA. Agents are prompted to supply hyperlinks or other information pertaining to access of remote or networked information when adding a remotely stored item to the archive. The MDPSA provides references for information discovered and supplied by its computational processing methods. In one embodiment, web locations of remote items are graphically displayed in a network representation that depicts not only access references, but also the relationships between information items. [0347 - schedule of tasks] End: Time-phased schedule of tasks [0047 - problem-solving activity proceeds and they capture an action plan for resolving the situation] Outputs are generated to support decision making and sense making They constrain the direction in which the problem-solving activity proceeds and they capture an action plan for resolving the situation. Process outputs are created by agent selections in the course of defining, exploring, resolving and envisioning the circumstances a complex problem. In one embodiment, process outputs take the form of lists of alternative ideas, or graphic displays. For example, a means-end hierarchy graphic could be generated to depict the causes of a problem and the relationship of aggravating problems that proceed there from. In another embodiment, process outputs take the form of stories that are depicted via text or audio verbal channels or by static or graphic animations. For example, an agent could supply a video animation that captures the result of a mental simulation. In another embodiment, process outputs take the form of a time-phased set of activities and tasks, e.g., a Gantt Chart.).
Deal 2014/0101079 may not expressly disclose the “scheduling system for scheduling repairs” features, however, Castel et al. 2014/0164603 teaches these features as follows (Castel et al. 2014/0164603 [0108 - messaging utility (62) may be utilized to send in-platform messages to the user's network through the platform (10) with a question as to who may know how to repair a broken machine] The platform (10) also may include a messaging utility (62) that enables users to share information or collaborate with colleagues or friends established using the social networking features of the social networking platform (16) (for example users may select as friends in their network established through the platform (10) only those individuals that they are comfortable or are not with a competing organization for example. The messaging utility (62) may be utilized to send in-platform messages to the user's network through the platform (10) with a question as to who may know how to repair a broken machine. [0129 - Predict and intelligently recommend the proper maintenance schedules, tasks and lists to users who desire such information based on equipment usage or queries asked] (F) Predict and intelligently recommend the proper maintenance schedules, tasks and lists to users who desire such information based on equipment usage or queries asked, and offer recommendations to optimize their processes, including procurement of parts, equipment, etc. or offering specialized data intelligence. [0131 - construct and obtain answers to various queries] The analytics engine (122) may enable an administrator for example to construct and obtain answers to various queries, or initiate the generation of various reports based on data output from the analytics engine (122). [0215 - platform is provided that predicts and intelligently recommends the proper maintenance schedules, tasks and lists to platform clients who desire such information based on equipment usage or queries asked, and offer recommendations to optimize their processes, including procurement of parts, equipment, etc] A platform is provided that predicts and intelligently recommends the proper maintenance schedules, tasks and lists to platform clients who desire such information based on equipment usage or queries asked, and offer recommendations to optimize their processes, including procurement of parts, equipment, etc or offering specialized data intelligence.). Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to have modified Deal 2014/0101079 to include the features as taught by Castel et al. 2014/0164603. One of ordinary skill in the art would have been motivated to do so to implement well tools and features useful for increasing query-answering agent accuracy which should prove to improve user experience, maximize profits, and optimize revenue (i.e., advertisement optimization / improve user experience).
18/911,074 – Claim 11. A computer-implemented method comprising: responsive to receiving a query related to an industrial unit and using at least one processor, generating a consultation prompt based on the query; retrieving, using a consultation agent, a response to the query; generating, based on the response, an evaluation prompt; retrieving, using an evaluation agent, an evaluation of the response; based on determining that the evaluation of the response is positive, generating a summarization prompt based on the response; retrieving, using a summarization agent, a response summary; and storing the response summary in a response set used to generate an answer comprising a repair plan, the answer to be transmitted to a scheduling system for scheduling repairs to the industrial unit.
Claim 11, has similar limitations as of Claim(s) 1, therefore it is REJECTED under the same rationale as Claim(s) 1.
18/911,074 – Claim 20. A non-transitory computer-readable storage medium, the computer-readable storage medium including instructions that when executed by a computer, cause the computer to: responsive to receiving a query related to an industrial unit, generate a consultation prompt based on the query; retrieve, using a consultation agent, a response to the query; generate, based on the response, an evaluation prompt; retrieve, using an evaluation agent, an evaluation of the response; responsive to determining that the evaluation of the response is positive, generate a summarization prompt based on the response; retrieve, using a summarization agent, a response summary; and store the response summary in a response set used to generate an answer comprising a repair plan, the answer to be transmitted to a scheduling system for scheduling repairs to the industrial unit.
Claim 20, has similar limitations as of Claim(s) 1, therefore it is REJECTED under the same rationale as Claim(s) 1.
Claims 2 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over: Deal 2014/0101079; in view of Castel et al. 2014/0164603; in further view of Krishna et al. 2016/0086114.
18/911,074 – Claim 2. Deal 2014/0101079 further teaches The system of claim 1, wherein: the response set comprises a predetermined minimum number of response summaries, the response summaries generated by a plurality of summarization agents, the response summaries corresponding to responses generated by a plurality of consultation agents, the responses evaluated by a plurality of evaluation agents (Deal 2014/0101079 [0051] Agents use metadata as a tool for identifying and retrieving information. Agent needs for metadata vary by the criteria they use to select information item. For example, a machine agent may seek to access a stored piece of information by data type or data size. Human agents may employ semantics or contextual cues as aids to associative retrieval. In one embodiment, human and machine participants and the MDPSA apply metadata to information articles for the purpose of retrieval. Examples of metadata include information-item creation name, keywords, data type, author name, thumbnail representations, creation date, agent name, contribution date and time, scoring, and number of times the information article was accessed. In one embodiment, agents assign a score to an information item to indicate its usefulness or lack of utility in supporting a problem solving activity. For example, a five-point Likert scale could be used to score an item, or a polar assessment of `useful` or `not useful` could be assigned. [0073] The MDPSA implements methods of natural language processing and graphics processing to reduce the cognitive and processing load on agents. In one embodiment, natural language and graphics processing are employed to extract attributes from individual agent inputs. For example, an agent might submit an audio recording of a verbal response to a question posed by the MDPSA. Computational linguistics methods would convert the audio response to text, and extract content attributes, such as meaning, intent, context, or emotional content. In one embodiment, extracted attributes are used to perform pairwise comparisons of agent inputs, and to identify and cull from a dialogue those that are substantially or statistically identical. For example, a graphics processing algorithm would compare two photos and determine that the two photos are the same with a high degree of probability. The existence of a duplicate photo would be indicated to agents, but only one photo would be displayed. In one embodiment, natural language and graphics processing methods are used to summarize entire dialogues. Summaries enable agents to review an abstracted version of a dialogue, and would thus mitigate information overload. In one embodiment, the content of an information-item archive is used to train natural language and graphical processing methods. Training can improve method performance, and helps with identifying attributes relevant to the complex problem. [0082] The MDPSA takes advantage of the polarity in motivation to encourage positive practices that enhance collaborative problem solving and to discourage negative practices that are detrimental to outcomes. Extrinsic rewards can be based on the agent contributions and observable behaviors. Agent performance can be scored in the virtual world in such a way that agent reputations in the real world are enhanced. Enhanced reputations can translate into real-world rewards. In one embodiment, a scoring algorithm is used to assess agent contributions. The algorithm incorporates quantitative information such as number and frequency of contributions, number of consecutive contributions, and first contributions to a dialogue. For example, high numbers of contributions that are frequently provided is indicative of engagement; these contribute to higher scores. A high number of consecutive contributions are indicative of dominance behavior which contributes to a lower score. A high number of individual responses to the contributions of others is indicative of collaborative behavior that contributes to a higher score. The scoring algorithm also incorporates qualitative information such as obscurity of expression as evidenced, for example, by overuse of acronyms. In one embodiment, linguistic and graphical analyses evaluate individual contributions to determine if detrimental behaviors, such as directive, authoritative, disrespectful, impatient, insulting, or profane practices are evidenced; these contribute to a lower score. Linguistic and graphical analyses also assess individual contributions for common argument errors and fallacies such as appeals to ignorance or equivocation; these contribute to a lower score. [0083] In one particular embodiment, agents receive three scores. The first score is based on their performance in a single MDPSA instance. This score drives players to excel in the extant instance. A second score is based on performance over all MDPSA instances in which an agent has participated. This score is an indicator of general problem solving skill. A third score represents an agent's expertise in a particular discipline or subject area. The third score is calculated by examining an agent's contribution in a specific expertise area, such as power generation or education, over all instances in which the agent provided expertise in that discipline. Evidence of contribution influence is also included in the expertise calculation. In one embodiment, influence is determined by natural language processing or graphical analyses that assess whether an agent's contribution served as an organizing principle around which other contributions were arranged. Expertise can also be recognized by other participants as a breakthrough. In one embodiment, peer assessments contribute positively and negatively to the expertise score. [0084] Scores can translate into tangible, extrinsic rewards in the real world. For example, an employer could review MDPSA scores and choose to hire an agent to participate in an MDPSA instance. Employers could select agents based on the aforementioned lifetime score which is representative of an agent's effectiveness in solving complex problems. In one embodiment, expertise scores are used as the basis for a virtual employment process. Hiring entities specify a candidate's qualifications based on their MDPSA scoring. Alternately, agents use MDPSA scores to seek out job opportunities through the internet. The agent's MDPSA scores provide evidence of competency that is used by potential employers as an evaluation criterion. [0439] In one particular embodiment, agents scores are used to align agents with new instances, potential employers or customers. Players with high scores are autonomously recommended for participation in an extant instance based on an identified need for expertise in the instance. In one embodiment, instance stakeholders review ranked scores by expertise and chose to extend invitations to high-scoring agents. Invitations may be extended using embedded invitation functionality with and without offers of compensation or other incentives for participation. In one embodiment, agents use their scores to search for networked employment postings or other work opportunities that align with their expertise. Prospective employers and customers review agent scoring, and use it as evidence of qualification for an advertised need.).
Deal 2014/0101079 may not expressly disclose the “evaluation” features, however, Krishna et al. 2016/0086114 teaches these features as follows (Krishna et al. 2016/0086114 [0041] The vendor evaluation module 406I of the consulting core component layer may be used to evaluate a vendor on different functional parameters and the associated weightage for each vendor. The vendor evaluation module 406I generates a dashboard illustrating summary of the vendors evaluated. The vendors may be evaluated based on the different evaluation parameters (technical, commercial, brand value, program management capabilities) and consultant ratings. The module 406I may generate draft version of the vendor evaluation document based on the responses from different vendors. The vendor evaluation may be done based on the question and response process in the data collection module.). Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to have modified Deal 2014/0101079 to include the features as taught by Krishna et al. 2016/0086114. One of ordinary skill in the art would have been motivated to do so to implement well tools and features useful for increasing query-answering agent accuracy which should prove to improve user experience, maximize profits, and optimize revenue (i.e., advertisement optimization / improve user experience).
18/911,074 – Claim 12. The method of claim 11, wherein the response set comprises a predetermined minimum number of response summaries, the response summaries generated by a plurality of summarization agents, the response summaries corresponding to responses generated by a plurality of consultation agents, the responses evaluated by a plurality of evaluation agents.
Claim 12, has similar limitations as of Claim(s) 2, therefore it is REJECTED under the same rationale as Claim(s) 2.
Claims 3 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over: Deal 2014/0101079; in view of Castel et al. 2014/0164603; in further view of Krishna et al. 2016/0086114; in view of Ferenczi 2025/0111141.
18/911,074 – Claim 3. Deal 2014/0101079 further teaches The system of claim 2, generating the answer further comprising: generating, based on the response summaries in the response set, an aggregation prompt; and retrieving, using an aggregation agent, the answer based on the response summaries (Deal 2014/0101079 [0032] The MDPSA incorporates supports to formal, group, problem solving and informal, individual, problem solving. It takes advantage of the experiential insights of individuals while providing structure that aggregates these insights and leads to closure. [0048] An aim of structured problem solving is to produce a communal understanding of a problematic situation. This aim is achieved through the exchange, access and retrieval of information contributions to the problem solving instance. In one embodiment, an archive of information items is included to extend agent memory capacities. In one embodiment a summary of information contributions is continuously updated and archived to support sense making and to mitigate information overload. Information items are stored for retrieval and reference over the network. [0049] Information items can be supplied to the archive in several ways. In one embodiment, agents supply materials by means of electronic transfer or upload. In one embodiment, agent inputs and outputs are placed in the archive by the MDPSA in the course of recording the contents of a dialogue or generating problem solving products. In one embodiment, background materials are discovered and supplied by MDPSA computational processing methods that drive search and retrieve capabilities. [0059] Groups of agents explore collective and contrasting perspectives and achieve consensus in accordance with facilitated dialogue methods. In one embodiment, a cycle of question, answer, clarification, selection, structuring and refinement is at the core of the process. Agents respond to questions and then engage in dialogue to clarify responses and achieve a common understanding of each response. Polling is used to select those answers that are perceived to have the greatest impact on the complex problem. Pairwise comparison is used to structure means-end relationships among clarified ideas. Agents review graphic depictions of relationships and engage in dialogues to suggest modifications that refine outputs as represented in the graphic representations. [Claim 14] 14. An information-overload mitigation system which reduces the information processed by human agents and artificial intelligence agents interacting with and within a network-based, internet-scale problem solving system to a level which requisite parsimony constraints are satisfied without sacrificing the requisite variety necessary for complex-problem solution, comprising: an information storage and retrieval system in which agent inputs are managed; natural language processing algorithms; said natural language processing algorithms extract key words, proper names, phases, activities, shapes, symbols, meaning, intent, context and affective content attributes from agent inputs; said natural language processing algorithms performing pairwise, semantic comparisons between textual and audio agent inputs and identifying, tagging, sequestering, and eliminating inputs with identical content from agent inputs to the problem solving system; said natural language processing continually summarizing the aggregate content of agent inputs and presenting the summary to agents; graphics processing algorithms; said graphics processing algorithms performing pairwise comparisons between graphical and video agent inputs and identifying, tagging, sequestering, and eliminating inputs with identical content from agent inputs to the problem solving system.).
Deal 2014/0101079 may not expressly disclose the “aggregation” features, however, Ferenczi 2025/0111141 teaches these features as follows (Ferenczi 2025/0111141 [0021] Once the distributed agent 118 receives the accurate response 109 from the one or more similarity detection services, the distributed agent 118 can provide the accurate response 109 to the client device 103 for rendering or otherwise displaying. In some examples, if there are multiple similar but not identical accurate responses 109 provided to the distributed agent 118, the received responses can be aggregated to provide a more comprehensive response to the prompt 112.). Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to have modified Deal 2014/0101079 to include the features as taught by Ferenczi 2025/0111141. One of ordinary skill in the art would have been motivated to do so to implement well tools and features useful for increasing query-answering agent accuracy which should prove to improve user experience, maximize profits, and optimize revenue (i.e., advertisement optimization / improve user experience).
18/911,074 – Claim 13. The method of claim 12, the method further comprising: generating, based on the response summaries in the response set, an aggregation prompt; and retrieving, using an aggregation agent, the answer based on the response summaries.
Claim 13, has similar limitations as of Claim(s) 3, therefore it is REJECTED under the same rationale as Claim(s) 3.
Claims 4 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over: Deal 2014/0101079; in view of Castel et al. 2014/0164603; in further view of Krishna et al. 2016/0086114.
18/911,074 – Claim 4. Deal 2014/0101079 further teaches The system of claim 2, wherein: an agent of a plurality of agents is at least one of the consultation agent, the evaluation agent, the summarization agent, or an aggregation agent (Deal 2014/0101079 [0050] Inputs can be stored either in a central location, in multiple locations, or by reference. Information that is frequently updated by authoritative sources, such as population data, national debt figures, or salary information is stored by reference to ensure the most recent updates are available to support problem solving activities. In one embodiment, virtual references to remotely stored information items are included in the archive. For example, remote information recorded as a web site or stored in a networked database could be accessed by agents through file transfer protocols, hyperlinks or other access means. References are generated by agents and by the MDPSA. Agents are prompted to supply hyperlinks or other information pertaining to access of remote or networked information when adding a remotely stored item to the archive. The MDPSA provides references for information discovered and supplied by its computational processing methods. In one embodiment, web locations of remote items are graphically displayed in a network representation that depicts not only access references, but also the relationships between information items. [0061] In one embodiment, the MDPSA requests agents to consider the avenues (legal, technology, information approaches) through which a problem could be addressed. Individual decision making is implemented by asking agents to recall the avenues they have found to be effective in similar situations, and to tell the story of how the implementation worked. Group decision making is implemented by polling agents for a preferred avenue based on stories of past successes. In one embodiment, individual decision making is implemented by prompting agents to imagine solutions implemented through an avenue, and to describe and submit their mental simulations. Group decision making is implemented by facilitating dialogues about each simulation, and by polling agents to select preferred avenue based on perceived story relevance to the extant problematic situation and on discussion content. [0424] Progress through the steps is facilitated by a combination of MDPSA prompts and participating agent selections as shown in FIG. 9. Facilitation is implemented as described by Warfield, Christakis, Delbecq, Van de Ven and Gustafson, and Pergamit and Peterson. Facilitation is comprised of set-up facilitation and process facilitation. In one embodiment, initiation of an instance is accomplished by means of a wizard which uses a recipe-like guide to set up of the problem-solving process. The products of the recipe are descriptions of the context of a problematic situation and the constraints which influence execution of a problem-solving process. In one embodiment, initiation of the re-planning process is accomplished with a wizard. The re-planning wizard proceeds summarily through the first six steps of the process allowing an agent re-starting an instance to assess the steps which need to be revisited. [Claims 1 and 2] 1. A knowledge processing system that enables massive numbers of human agents and artificial intelligence agents to define, explore, and develop a solution for a problematic situation, where massive is bounded by the number of agents on the internet worldwide, comprising: an electromagnetic communications network; client devices that enable human and artificial intelligence agents to supply inputs to the knowledge processing system and receive outputs from the knowledge processing system over said network; said client devices configurable to provide private workspaces for agents from which other agents are precluded and public workspaces in which agents jointly work; an information storage and access system for managing knowledge processing system outputs and agent inputs; a facilitation system configured to guide agents through the exercise of problem-solving steps; said steps are problem definition, identification of the topical information domains of which the problematic situation is comprised, exploration of the problematic situation, definition of solution approaches, selection of a solution approach from those defined by agents, description of the solution approaches, and time-sequenced action plan creation; said facilitation system presents to agents for selection as solution approaches technological, investment, engineering, data mining, experiment, information campaigning, organizational change, regulatory change, research, additional expertise, statutory change, education, marketing, quality improvement, and visioning approaches; said problem-solving exercise is comprised of parent forums in which the problematic situation is considered as a whole and child forums in which the problematic situation is considered in parts as described by agent-identified, topical-information domains; said facilitation system decomposes the problematic-situation exploration step and the solution-definition step into child forums, one child forum for each topical-information domain of which the problematic situation is comprised; said facilitation system guides agents in the synthesis and relation of problematic-situation exploration child forum findings into a holistic representation of the problematic situation; said facilitation system guides agents in the synthesis and relation of solution-defining, child-forum findings into an integrated solution comprised of solutions that address sub problems of the problematic situation that are peculiar to topical-information domains; said facilitation system automatically assigns agents to participate in child forums based on self-identified expertise and interests elicited from agents by the system; said facilitation system transmits input prompts to agents; some of said input prompts direct agents to provide a description of the problematic situation; some of said input prompts direct agents to provide a description the temporal and financial constraints and goals of the problem-solving situation; some of said input prompts direct agents to select questions from a list of questions maintained in said data storage system; some of said input prompts direct agents to submit answers to questions; some of said input prompts direct agents to clarify answers in a dialogue format; some of said input prompts direct agents to select answers from among those submitted by agents; some of said prompts direct agents to preferentially rank answers; said data storage system configured to associate agent responses with system-generated prompts; said data storage system configured to store agent responses to prompts; said storage and access system aggregating system outputs and agent inputs so they can be reused in whole or in part by other implementations of the system for other problematic situations; said facilitation system enforces agent-defined, time constraints of the problem-solving exercise.).
18/911,074 – Claim 14. The method of claim 12, generating the answer further comprising: an agent of a plurality of agents is at least one of the consultation agent, the evaluation agent, the summarization agent, or an aggregation agent.
Claim 14, has similar limitations as of Claim(s) 4, therefore it is REJECTED under the same rationale as Claim(s) 4.
Claims 5 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over: Deal 2014/0101079; in view of Castel et al. 2014/0164603; in further view of Krishna et al. 2016/0086114.
18/911,074 – Claim 5. Deal 2014/0101079 further teaches The system of claim 2, wherein: each consultation agent of the plurality of consultation agents is bound to a bound evaluation agent of the plurality of evaluation agents, the respective consultation agent being different from the bound evaluation agent; and each consultation agent of the plurality of consultation agents is bound to a bound summarization agent of the plurality of summarization agents, the respective consultation agent being different from the bound summarization agent (Deal 2014/0101079 [0424] Progress through the steps is facilitated by a combination of MDPSA prompts and participating agent selections as shown in FIG. 9. Facilitation is implemented as described by Warfield, Christakis, Delbecq, Van de Ven and Gustafson, and Pergamit and Peterson. Facilitation is comprised of set-up facilitation and process facilitation. In one embodiment, initiation of an instance is accomplished by means of a wizard which uses a recipe-like guide to set up of the problem-solving process. The products of the recipe are descriptions of the context of a problematic situation and the constraints which influence execution of a problem-solving process. In one embodiment, initiation of the re-planning process is accomplished with a wizard. The re-planning wizard proceeds summarily through the first six steps of the process allowing an agent re-starting an instance to assess the steps which need to be revisited. [0429] In one embodiment metadata provided by agents and discovered by natural language and graphics processing algorithms are coupled with instance background material. Background material is stored in an archive and is indexed by metadata that enable retrievable and use by human and machine agents. Human-agent indexing enables associative cognitive processes to be applied to background material. In one particular embodiment, background material is brought to the attention of agents in dialogues by aligning metadata extracted from dialogues with metadata extracted from a background item. Machine-agent indexing includes file attributes and processing attributes that enable machines agents to download, open, and process archive items. In one particular embodiment, metadata includes agent appraisals of reference items. In one embodiment, the MDPSA appraisals indicative of the influence an information artifact has had on agents, on individual dialogues, and on the whole instance are included among metadata associated with background material. Influence is indicated by the number of agents accessing the item, the total number of times an item was accessed, the number of child dialogues in which the item was mentioned, or the number of parent dialogues in which the item was mentioned. [Claims 1 and 2]).
18/911,074 – Claim 15. The method of claim 12, wherein: each consultation agent of the plurality of consultation agents is bound to a bound evaluation agent of the plurality of evaluation agents, the respective consultation agent being different from the bound evaluation agent; and each consultation agent of the plurality of consultation agents is bound to a bound summarization agent of the plurality of summarization agents, the respective consultation agent being different from the bound summarization agent.
Claim 15, has similar limitations as of Claim(s) 5, therefore it is REJECTED under the same rationale as Claim(s) 5.
Claims 6 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over: Deal 2014/0101079; in view of Castel et al. 2014/0164603.
18/911,074 – Claim 6. Deal 2014/0101079 further teaches The system of claim 1, wherein: generating the consultation prompt further comprises the use of a consultation prompt template; generating the evaluation prompt further comprises the use of an evaluation prompt template; and generating the summarization prompt further comprises the use of a summarization prompt template (Deal 2014/0101079 [0424] Progress through the steps is facilitated by a combination of MDPSA prompts and participating agent selections as shown in FIG. 9. Facilitation is implemented as described by Warfield, Christakis, Delbecq, Van de Ven and Gustafson, and Pergamit and Peterson. Facilitation is comprised of set-up facilitation and process facilitation. In one embodiment, initiation of an instance is accomplished by means of a wizard which uses a recipe-like guide to set up of the problem-solving process. The products of the recipe are descriptions of the context of a problematic situation and the constraints which influence execution of a problem-solving process. In one embodiment, initiation of the re-planning process is accomplished with a wizard. The re-planning wizard proceeds summarily through the first six steps of the process allowing an agent re-starting an instance to assess the steps which need to be revisited. [0429] In one embodiment metadata provided by agents and discovered by natural language and graphics processing algorithms are coupled with instance background material. Background material is stored in an archive and is indexed by metadata that enable retrievable and use by human and machine agents. Human-agent indexing enables associative cognitive processes to be applied to background material. In one particular embodiment, background material is brought to the attention of agents in dialogues by aligning metadata extracted from dialogues with metadata extracted from a background item. Machine-agent indexing includes file attributes and processing attributes that enable machines agents to download, open, and process archive items. In one particular embodiment, metadata includes agent appraisals of reference items. In one embodiment, the MDPSA appraisals indicative of the influence an information artifact has had on agents, on individual dialogues, and on the whole instance are included among metadata associated with background material. Influence is indicated by the number of agents accessing the item, the total number of times an item was accessed, the number of child dialogues in which the item was mentioned, or the number of parent dialogues in which the item was mentioned. [Claims 1 and 2]).
18/911,074 – Claim 16. The method of claim 11, wherein: generating the consultation prompt further comprises the use of a consultation prompt template; generating the evaluation prompt further comprises the use of an evaluation prompt template; and generating the summarization prompt further comprises the use of a summarization prompt template.
Claim 16, has similar limitations as of Claim(s) 6, therefore it is REJECTED under the same rationale as Claim(s) 6.
Claims 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over: Deal 2014/0101079; in view of Castel et al. 2014/0164603.
18/911,074 – Claim 7. Deal 2014/0101079 further teaches The system of claim 1, wherein storing the response summary in the response set further comprises storing an entry corresponding to the consultation agent in the response set, the entry comprising one or more of an identifier of the consultation agent, a response status, the response, and the response summary (Deal 2014/0101079 [0087] In one embodiment, the MDPSA implements an archive that stores, in summary and complete form, the dialogues, background materials, attribute lists, participants, participant scores, and products of an MDPSA instance. The archive includes agent-generated and MDPSA-generated metadata that enables agents to identify and access materials from historic instances that are relevant to a contemporary instance. For example, an entire instance can be cloned for the purpose of modifying products that addressed a similar problematic situation. Additionally, agents can select a single dialogue for insertion into another instance. Agents could conceivably create a new instance by combining select dialogues of prior instances. Archived participant scores can be used as a filter for inviting effective participants to join a new or re-initiated instance. [0431] In one embodiment, an instance archive stores a complete set of instance artifacts including culled duplicate entries. The instance archive is organized such that an entire instance or individual parts can be retrieved for subsequent modification or can be cloned for alternate use. Child forum dialogues that address problems and solutions are discretely archived in order that materials related to constituent dimensions of an instance can be retrieved and reused in other instances. In one particular embodiment, the MDPSA analyzes an active instance, and recommends historic, archived dimensional dialogues for inclusion in the extant problem-solving process. In one embodiment, archived materials are appended with the names of other instances into which they have been incorporated. This provides heritage traceability, and enables agents to ascertain relationships between complex problems.).
18/911,074 – Claim 17. The method of claim 11, wherein storing the response summary in the response set further comprises storing an entry corresponding to the consultation agent in the response set, the entry comprising one or more of an identifier of the consultation agent, a response status, the response, and the response summary.
Claim 17, has similar limitations as of Claim(s) 7, therefore it is REJECTED under the same rationale as Claim(s) 7.
Claims 8 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over: Deal 2014/0101079; in view of Castel et al. 2014/0164603.
18/911,074 – Claim 8. Deal 2014/0101079 further teaches The system of claim 7, wherein the response status is at least one of at least pending, received, responsive, non-responsive, or timed out (Deal 2014/0101079 [0126] Determine time durations for responses to questions).
18/911,074 – Claim 18. The method of claim 17, wherein the response status is at least one of at least pending, received, responsive, non-responsive, or timed out.
Claim 18, has similar limitations as of Claim(s) 8, therefore it is REJECTED under the same rationale as Claim(s) 8.
Claims 9 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over: Deal 2014/0101079; in view of Castel et al. 2014/0164603; in further view of Krishna et al. 2016/0086114; in view of Ferenczi 2025/0111141.
18/911,074 – Claim 9. Deal 2014/0101079 further teaches The system of claim 3, wherein retrieving the answer based on response summaries comprises: identifying one or more elements included in a predetermined proportion of the response summaries; and generating the answer to include the one or more identified elements (Deal 2014/0101079 [0059] Groups of agents explore collective and contrasting perspectives and achieve consensus in accordance with facilitated dialogue methods. In one embodiment, a cycle of question, answer, clarification, selection, structuring and refinement is at the core of the process. Agents respond to questions and then engage in dialogue to clarify responses and achieve a common understanding of each response. Polling is used to select those answers that are perceived to have the greatest impact on the complex problem. Pairwise comparison is used to structure means-end relationships among clarified ideas. Agents review graphic depictions of relationships and engage in dialogues to suggest modifications that refine outputs as represented in the graphic representations. [0068] The MDPSA is rooted in the premise that the emphasis higher education and work roles place on specialization leaves people ill-prepared to synthesize solutions to complex problems. As a result, human agents are more likely consider only the influences their area of expertise exerts on other dimensions of a complex problem. Similarly, machine-agent data structures are designed to relate elements contained in a data structure, but fall short of creating meaning from stored data integrated across information domains. [0099] In one particular embodiment of the invention, problem solving progresses through the six steps shown in FIG. 2 that result in an action plan. A seventh step is included for adjusting the products of the six steps or for modifying the action plan. While it is advantageous to approach problem-solving in these steps sequentially, the invention is flexible. Problem solving can involve overlapping steps and certain steps may need to be repeated or readdressed as part of other steps. For example, the progression from establishing the scope of a problematic situation to exploration of the situation to generation of a resolution plan would follow developments as they are exposed in the literature. However, learning that occurs during the solution-generation step may reveal new dimensions of the problematic situation that need to be explored. It would thus be advantageous to revisit earlier steps. Each step has specific products which agents will employ in subsequent steps. Distinct dialogue elements provide opportunities for collaborative learning that help the group to devise, evaluate, and compare solutions, and to develop an action plan to address the problematic situation. Facilitation serves the needs of the participating agents and eases progress toward common goals. [Claim 1]).
18/911,074 – Claim 19. The method of claim 13, wherein retrieving the answer based on response summaries comprises: identifying one or more elements included in a predetermined proportion of the response summaries; and generating the answer to include the one or more identified elements.
Claim 19, has similar limitations as of Claim(s) 9, therefore it is REJECTED under the same rationale as Claim(s) 9.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over: Deal 2014/0101079; in view of Castel et al. 2014/0164603.
18/911,074 – Claim 10. Deal 2014/0101079 further teaches The system of claim 1, wherein retrieving the response to the query using the consultation agent comprises waiting for the response for a predetermined maximum time period (Deal 2014/0101079 [0101] The seven steps of one embodiment of the invention are described in outline form below. Details of steps one through six of this embodiment are provided in FIG. 3. It will be noted that in this embodiment of the invention, the first step objectives are a description of the circumstances surrounding a complex problem and a description of conditions that constrain execution of the problem solving process. The second step objectives are to decompose the problematic situation into dimensions, facets, or domains of which the complex problem is comprised, and to identify the knowledge or expertise needed to investigate the complex problem. The third step objectives are to identify problems that must be addressed in each of the dimensions, to build a model of means-end relationships between the problems in one dimension, and to relate the problems identified in one dimension to those of all the other dimensions. The fourth step objectives are to select approaches by which the complex problem will be addressed, and to identify interdependencies between selected approaches. The fifth step objectives are to generate solutions for the identified problems, to build a model of the means-end relationships between the solutions to problems in one dimension, and to relate the solutions from one dimension with those of all the other dimensions. The sixth step objective is to generate a time-phased, action plan for enacting a solution. The seventh step objectives are to revise products and decisions made in previous steps, and to modify the time-phased action plan. The following outline describes steps embodiments of the invention support. [0126] Determine time durations for responses to questions).
Examiner’s Response to Arguments
Per Applicants’ amendments/arguments, the rejections are withdrawn.
Applicant's arguments have been considered but are moot in view of the new ground(s) of rejection.
Applicants’ amendments have necessitated the new grounds of rejection noted above.
Examiner’s Response: Claim Rejections – 35 USC §112
Per Applicants’ amendments/arguments, the rejections are withdrawn.
Applicant's arguments have been considered but are moot in view of the new ground(s) of rejection.
Applicants’ amendments have necessitated the new grounds of rejection noted above.
Examiner’s Response: Claim Rejections – 35 USC §101
Per Applicants’ amendments/arguments, the rejections are withdrawn. See notes above for additional reasoning and rationale for dropping 35 USC 101 rejection including Applicant’s amendments, arguments, lack of abstract idea, and practical integration.
Applicant's arguments have been considered but are moot in view of the new ground(s) of rejection.
Applicants’ amendments have necessitated the new grounds of rejection noted above.
Regarding Claims 1-15, on page(s) 6-12 of Applicant’s Remarks (dated 12/27/2016), Applicants traverse the 35 USC §101 rejections arguing the following:
Examiner’s Response: Claim Rejections – 35 USC § 102 / § 103
Per Applicants’ amendments/arguments, the rejections are withdrawn. See notes above for additional reasoning and rationale for dropping prior-art rejection including Applicant’s amendments and arguments and unique combination of features and elements not taught by the prior-art without hindsight reasoning.
Applicant's arguments have been considered but are moot in view of the new ground(s) of rejection.
Applicants’ amendments have necessitated the new grounds of rejection noted above.
Regarding Claim X, on page(s) 8-9 of Applicant’s Remarks / After Final Amendments (dated 07/15/2011), Applicant(s) argues that the cited reference(s) (Ellis and Vandermolen) fails to teach, describe, or suggest the amended features. Specifically, Applicant(s) argues that cited reference(s) do not teach, describe, or suggest the following: . With respect, Applicant’s arguments are deemed unpersuasive and the amended feature(s) remain rejected as follows.
With respect, Applicant’s arguments are deemed unpersuasive and the amended feature(s) remain rejected as follows.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
PERTINENT PRIOR ART – Patent Literature
The prior-art made of record and considered pertinent to applicant's disclosure.
Full et al. 2022/0405664 [0037 - inquiry has been received… the action module 70 may provide suggestions in step 210 when scheduling a consultation, and/or when determining how to respond if step 206 determines that no consultation date has been scheduled]
Wilson 2011/0298629 [0004 - a system for scheduling maintenance on mechanical equipment]
Uyeki 2009/0089134 [0034 - a system and method for proactively scheduling vehicle service appointments]
Hua et al. 2016/0005242 [0022 - Automatically schedules maintenance]
Mansfield et al. 2017/0004508 [0004 - appliance automatically notifies the automated service provider, who then determines the failure and dispatches a service technician skilled in the necessary repair trade]
Mazur et al. 2024/0163295 [0081 - coordinate across maintenance schedule for variety of devices]
PERTINENT PRIOR ART – Non-Patent Literature (NPL)
The NPL prior-art made of record and considered pertinent to applicant's disclosure.
The BEST NPL prior-art reference is:
Other relevant NPL prior-art reference are:
Conclusion
THIS ACTION IS MADE FINAL
Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
THIS ACTION IS MADE FINAL
Applicant’s amendment necessitated new grounds of rejection and FINAL Rejection.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW T. SITTNER whose telephone number is (571) 270-7137 and email: matthew.sittner@uspto.gov. The examiner can normally be reached on Monday-Friday, 8:00am - 5:00pm (Mountain Time Zone). Please schedule interview requests via email: matthew.sittner@uspto.gov
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sarah M. Monfeldt can be reached on (571) 270-1833.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MATTHEW T SITTNER/
Primary Examiner, Art Unit 3629b