DETAILED ACTION
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 .
Request for Information Under 37 CFR § 1.105
37 C.F.R. 1.105 Requirements for information.
(a)
In the course of examining or treating a matter in a pending or abandoned application, in a patent, or in a reexamination proceeding, including a reexamination proceeding ordered as a result of a supplemental examination proceeding, the examiner or other Office employee may require the submission, from individuals identified under § 1.56(c), or any assignee, of such information as may be reasonably necessary to properly examine or treat the matter, for example:
Commercial databases: The existence of any particularly relevant commercial database known to any of the inventors that could be searched for a particular aspect of the invention.
Search: Whether a search of the prior art was made, and if so, what was searched.
Related information: A copy of any non-patent literature, published application, or patent (U.S. or foreign), by any of the inventors, that relates to the claimed invention.
Information used to draft application: A copy of any non-patent literature, published application, or patent (U.S. or foreign) that was used to draft the application.
Information used in invention process: A copy of any non-patent literature, published application, or patent (U.S. or foreign) that was used in the invention process, such as by designing around or providing a solution to accomplish an invention result.
Improvements: Where the claimed invention is an improvement, identification of what is being improved.
In Use: Identification of any use of the claimed invention known to any of the inventors at the time the application was filed notwithstanding the date of the use.
Technical information known to applicant. Technical information known to applicant concerning the related art, the disclosure, the claimed subject matter, other factual information pertinent to patentability, or concerning the accuracy of the examiner’s stated interpretation of such items.
Requirements for factual information known to applicant may be presented in any appropriate manner, for example:
A requirement for factual information;
Interrogatories in the form of specific questions seeking applicant’s factual knowledge; or
Stipulations as to facts with which the applicant may agree or disagree.
Any reply to a requirement for information pursuant to this section that states either that the information required to be submitted is unknown to or is not readily available to the party or parties from which it was requested may be accepted as a complete reply.
The requirement for information of paragraph (a)(1) of this section may be included in an Office action, or sent separately.
A reply, or a failure to reply, to a requirement for information under this section will be governed by §§ 1.135 and 1.136.
Throughout the specification references are made to the following publications that are incorporated by reference into the specification: see at least (1) [0027] Bringsjord et al., “Logic-Based Modeling of Cognition”; (2) [0032] Bringsjord et al., “Automated Argument Adjudication…”; (3) [0044] Bringsjord et al. “Learning in Ex Nihilo”; and (4) [0048] Govinfarajulu et al. “On Automating the Doctrine of Double Effect.” These documents were not listed on an IDS and copies were not provided to the Office. Each of these documents has information that could be used to retrieve copies including URLs, however the information is either inaccurate or outdated.
Please present updated accurate citations for each of these 4 documents, please also supply copies of each of these documents.
Claim Objections
Claim 13 is objected to because of the following informalities: “A artificially intelligent method”. Appropriate correction is required.
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 because the claims are directed to a judicial exception, in this case the exception is an abstract idea (see MPEP 2016.03).
Independent Claims 1 and 13
Step 2A – Prong One:
The limitations of these claims recite the generation of an emergency response plan, including the following steps:
translating event information
selecting a meta-model that conforms to the emergency event
generating a hypergraph, a goal, and a plan based upon received event information
These limitations recite a certain method of organizing human activity because these process steps are regularly performed by emergency response dispatchers when answering emergency calls to gather information, determine which rules and models apply and create a response plan. Alternatively, the limitations also recite a mental process, specifically performing a mental process in a computer environment (see MPEP 2016.04(a)(2)) to assist with the generation of an emergency response plan including collecting information, analyzing it, and displaying certain results. Claims 1 and 13 recite an abstract idea.
Step 2A – Prong Two:
The scope of the independent claim limitations incorporate the following additional elements:
A memory and a processor coupled to the memory
One or more input devices and an output device
Selecting a meta-model
Generating a hypergraph model from a meta-model
Outputting the plan on an output device
Emergency event and semantic information
These additional elements listed above, or combination of these elements, amount to nothing more than simply reciting the abstract idea while adding the words ‘apply it’, MPEP 2106.05(f). The system elements, a memory and a processor coupled to the memory, one or more input devices and an output device to implement the abstract idea amount to mere instructions to apply it using generic computer components. Further additional elements that recite generally implemented computer processes, like selecting a meta-model or generating a hypergraph from the meta-model, are recited at a high level of generality amount to nothing more than instructions to apply the abstract idea without any improvement to technology, technical field, or to the functioning of the computer itself.
Therefore, the additional elements, whether evaluated individually or in combination, fail to integrate the recited abstract idea into a practical application. The claimed invention is directed to an abstract idea.
Step 2B
Under Step 2B of the patent eligibility analysis, the combination of additional elements is evaluated to determine whether they amount to something “significantly more” than the recited abstract idea of routing customer consultation requests. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
Claims 1 and 13 are not patent eligible.
Dependent Claims –
Claims 2 and 14 recite the abstract idea to analyze new event information to determine whether the current model is viable and generate a new model if the current model is no longer viable, which are mental processes. The claim limitations are directed to an abstract idea without significantly more.
Claims 3 and 15 further recite the abstract idea to analyze new event information to determine whether the current model is viable and generate a new model if the current model is no longer viable, which are mental processes. The claim limitations are directed to an abstract idea without significantly more.
Claims 4 and 16 recite the additional element, logically controlled natural language with cognitive calculi. This additional element, whether considered individually or in combination, is recited at a high level of generality and does not integrate the abstract idea into a practical application because these elements do not add significantly more to apply the abstract idea.
Claims 5 and 17 recite the additional elements, a hypergraph model including the nodes that compromise human and artificial agents. These additional elements, whether considered individually or in combination, are merely recited and does not integrate the abstract idea into a practical application because these elements do not add significantly more to apply the abstract idea.
Claims 6 and 18 recite the additional elements, the nodes of a hypergraph that include a function to define agent capability, formulae that define agent attributes and a set of agent dependencies. These additional elements, whether considered individually or in combination, are merely recited and does not integrate the abstract idea into a practical application because these elements do not add significantly more to apply the abstract idea.
Claims 7 and 19 further recite the abstract idea because the claim limitations recite a mental process, specifically performing a mental process in a computer environment (see MPEP 2016.04(a)(2)). The attributes, which includes agent beliefs, knowledge, intensions and perceptions, require opinions and judgment which is a mental process. The claim limitations are directed to an abstract idea without significantly more.
Claims 8 and 20 further recite the abstract idea because the claim limitations recite a mental process, specifically performing a mental process in a computer environment (see MPEP 2016.04(a)(2)). The assignment of a cognitive-likelihood value on new event information originating from a human requires opinions and judgment which is a mental process. The claim limitations are directed to an abstract idea without significantly more.
Claim 9 further recites the abstract idea because the claim limitations recite a mental process, specifically performing a mental process in a computer environment (see MPEP 2016.04(a)(2)). The assignment of a cognitive-likelihood value on new event information originating from a human requires opinions and judgment which is a mental process. The claim limitations are directed to an abstract idea without significantly more.
Claim 10 recites the additional element to display the plan as an annotated hypergraph onto an output device. This additional element, whether considered individually or in combination, is merely recited and does not integrate the abstract idea into a practical application because these elements do not add significantly more to apply the abstract idea.
Claim 11 recites the additional element, an annotated hypergraph contains geospatial information. This additional element, whether considered individually or in combination, is merely recited and does not integrate the abstract idea into a practical application because these elements do not add significantly more to apply the abstract idea.
Claim 12 recites the additional element, the hypergraph is periodically updated with new information. This additional element, whether considered individually or in combination, is merely recited and does not integrate the abstract idea into a practical application because these elements do not add significantly more to apply the abstract idea.
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 (i.e., changing from AIA to pre-AIA ) 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, 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.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Dupont et al, US Patent Application Publication US 2014/0096249 A1, herein referred to as “Dupont”, and further in view of Martin et al, US Patent Application Publication US 2020/0288295 A1, herein referred to as “Martin”.
Regarding Claims 1 and 13, Dupont teaches the following limitations:
translating the received event information into a logically controlled natural language
Dupont teaches (¶1408 and Fig. 45 – the behavior-based alert visualization, an actor is scored in view of a behavioral trait; in the example recited in the figure, actors are given a score relative to their association with the behavioral metric listed in the visual, which under BRI is interpreted to be controlled natural language because the event information is categorized into behavioral metrics)
generating a hypergraph model
Dupont teaches (¶0512 – the hypergraph system is designed to continuously add elements and may invoke incremental calculation s to update the derived structures in the hypergraph)
generating a goal
Dupont teaches (¶473 and Fig. 14 – data sampled by the system is reviewed and an analyst defines the performance targets of the categorization process)
based on the received event information
Dupont teaches (¶0462 – the categorization model is initially built on the knowledge engineering results, including defining and tuning ontology classifiers, as well as built on the reference data provided by the system)
generating a plan
Dupont teaches (¶0185 – the detected anomalies can trigger mitigating or preventative actions, which is interpreted as a plan because the anomaly detection component is developing actions to be completed based upon the incoming stream of events)
and outputting based on the hypergraph model, semantic information
Dupont teaches (¶1248 – the standard actor graph visualization displays actors, along with communication and other events as edges)
However, Dupont does not fully teach:
selecting a meta-model that conforms to the emergency event
but Martin teaches selecting a meta-model that conforms to the emergency event (¶0123 and Fig. 12 – the event correlation logic module determines the emergency network dispatch rule for the emergency type, which under BRI is interpreted to be a meta-model because a meta-model outlines a set of rules for each emergency event type similar to the emergency network dispatch rules recited above. For each event and the emergency correlation logic module will send dispatch recommendations based upon the emergency network dispatch rules to the entity designated in the emergency network dispatch rule)
generating a hypergraph model from the meta-model, wherein the hypergraph model includes details from the received event information
but Martin teaches from the meta-model (¶0123 and Fig. 12)
outputting to an output device, the goal, and semantic information
but Martin teaches outputting to an output device, the goal, and semantic information (¶0130, Fig. 8 and Fig. 15 – the emergency data manager sends dispatch information that is displayed on the responder device GUI)
Further, it would have been obvious to combine the teachings of Dupont above with methodology to select emergency dispatch rules for the specific emergency event type teaching, along with outputting the emergency response goal by Martin because Dupont states that its teachings can be applied to high-risk domains and one of ordinary skill would have recognized these could include emergency response domains.
Regarding Claims 2 and 14, Dupont and Martin teach the limitations above. Dupont and Martin teach the following limitations:
receiving new event information
Dupont teaches (¶0175 and Fig. 4 – the data collection component collects data continuously or in batch mode from a variety of data sources, extracts their content and stores the results for access by downstream systems)
translating the new event information to the logically controlled natural language
Dupont teaches (¶1408 and Fig. 45)
analyzing the new event information with an automated reasoner to determine whether a current model is viable
Dupont teaches (¶0492-93 and Fig. 14 – changes in detected topics, actors, and groups involved with the data can invoke as many changes as possible, including a new categorization component (model))
generating a new model if the current model is no longer viable
Dupont teaches (¶0492-93 and Fig. 14)
Regarding Claims 3 and 15, Dupont and Martin teach the limitations above. Dupont teaches the following limitations:
analyzing the new event information with the automated reasoner to determine whether a current plan is viable
Dupont teaches (¶0598-99 – the ad-hoc workflow analysis component detects ad-hoc workflows; a new workflow is built whenever a significant number of identified event sequences conform to a particular pattern)
generating a new plan if the current plan is no longer viable
Dupont teaches (¶0598-99)
Regarding Claims 4 and 16, Dupont and Martin teach the limitations above. Dupont teaches the following limitation:
wherein the logically controlled natural language is implemented with cognitive calculi
Under BRI, cognitive calculi is interpreted to be a formal system for modeling human cognition
Dupont teaches (¶0631-33 – the emotive analysis method distinguishes emotional expression from appraisal by using a variety of indicators, like lexical choice, tense distinctions; the emotive tone analysis component recognizes a set of basic emotions and cognitive states)
Regarding Claims 5 and 17, Dupont and Martin teach the limitations above. Dupont teaches the following limitation:
(Claim limitation recites neither a method, nor a system, as specified in the preamble. Rather it recites a data structure. However, under the principles of compact prosecution, the claim limitation will still be evaluated by the examiner.)
wherein the hypergraph model comprises nodes that represent human and artificial agents
Dupont teaches (¶0158 – an actor is a human or computer system that produces item)
Also refer to (¶1248 – the standard actor graph visualization displays actors (human or computer system as recited in ¶0158) as well as edges)
Regarding Claims 6 and 18, Dupont and Martin teach the limitations above. Dupont teaches the following limitations:
(Claim limitations recite neither a method, nor a system, as specified in the preamble. Rather they recite data structures. However, under the principles of compact prosecution, the claim limitations will still be evaluated by the examiner.)
a function that defines a percept to action capability of the agent
Dupont teaches (¶0644 – the range of any emotion can be modeled by the emotive tone analysis component)
a set of formulae in the logically controlled natural language that defines attributes of the agent; and
Dupont teaches (¶1408 and Fig. 45)
a set of dependencies that the agent depends upon
Dupont teaches (¶0823 – behavior traits are broken down into broad categories, including job performance and character traits)
Regarding Claims 7 and 19, Dupont and Martin teach the limitations above. Dupont teaches the following limitation:
(Claim limitation recites neither a method, nor a system, as specified in the preamble. Rather it recites a data structure. However, under the principles of compact prosecution, the claim limitation will still be evaluated by the examiner.)
wherein the attributes are configured to store beliefs, knowledge, intensions, and perceptions of the agent
Dupont teaches (¶0630-33 – a method and system identifies and analyzes subjective emotional expression occurrences in communications; the set of basic emotions and cognitive states include anger, surprise, fear, confusion and frustration)
Regarding Claims 8 and 20, Dupont and Martin teach the limitations above. Dupont teaches the following limitation:
(Claim limitation recites neither a method, nor a system, as specified in the preamble. Rather it recites a data structure. However, under the principles of compact prosecution, the claim limitation will still be evaluated by the examiner.)
wherein new event information originating from a human is assigned a cognitive-likelihood value
Dupont teaches (¶1377 – behavioral anomalies that were detected with a confidence and relevance level, likelihood to present harmful behavior, that exceeded a notification threshold will be displayed on the timeline visualization)
Regarding Claim 9, Dupont and Martin teach the limitations above. Dupont teaches the following limitation:
(Claim limitation recites neither a method, nor a system, as specified in the preamble. Rather it recites a data structure. However, under the principles of compact prosecution, the claim limitation will still be evaluated by the examiner.)
wherein the cognitive-likelihood value is utilized to evaluate viability of the current model and current plan
Dupont teaches (¶0167 – a predicted alert based on the likelihood of some events associated to anomalous behavior or patterns occurring in the future)
Regarding Claim 10, Dupont and Martin teach the limitations above. Dupont and Martin teach the following limitation:
wherein the plan is displayed on the output device as an annotated hypergraph
Dupont teaches (¶0544 – when problems are discovered with the algorithm, “fixes” are placed in the hypergraph; the system allows for an annotation to be placed on the respective alias atoms)
Regarding Claim 11, Dupont and Martin teach the limitations above. Dupont teaches the following limitation:
(Claim limitation recites neither a method, nor a system, as specified in the preamble. Rather it recites a data structure. However, under the principles of compact prosecution, the claim limitation will still be evaluated by the examiner.)
wherein the annotated hypergraph includes geospatial information
Dupont teaches (¶0994 – detected anomalies in emotive tones or entities could have categorical features, like geographical location, added)
Regarding Claim 12, Dupont and Martin teach the limitations above. Dupont teaches the following limitation:
wherein the annotated hypergraph is periodically updated with new event information
Dupont teaches (¶0435 – segments and disturbances are continuously indexed on time intervals to determine if there is a slightly modified index tree version; an extra annotation is added to every interval node to demonstrate the corresponding periodic pattern ID)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RAHUL SHARMA whose telephone number is (571) 272-3058. The examiner can normally be reached Monday thru Friday, 8-5 CT.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Nathan Uber can be reached at (571) 270-3923. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
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/RAHUL SHARMA/Examiner, Art Unit 3626
/NATHAN C UBER/Supervisory Patent Examiner, Art Unit 3626
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