DETAILED ACTION
Notice of Pre-AIA or AIA Status
[1] The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
[2] 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 10 February 2026 has been entered.
Notice to Applicant
[3] This communication is in response to the Amendment and the Request for Continued Examination (RCE) filed 10 February 2026. Claims 6, 14, and 17-20 have been cancelled. Claims 1, 9, 21, and 25 have been amended. Claims 1-5, 7-13, 15-16, and 21-26 are pending.
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.
[4] Previous rejection(s) of claims 1-5, 7-13, 15-16, and 21-26 under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter, specifically an abstract idea without significantly more has/have not been overcome by the amendments to the subject claims and is/are maintained. The revised statement of rejection presented below is necessitated by amendment and addresses the present amendments to the pending claims.
The following analysis is based on the framework for determining patent subject matter eligibility under 35 U.S.C. 101 established in the decisions of the Supreme Court in Mayo Collaborative Services v. Prometheus Labs., Incorporated and Alice Corporation Pty. Ltd. v. CLS Bank International, et al. (See MPEP 2106 subsection III and 2106.03-2106.05) the 2024 Guidance Update on Patent Subject Matter Eligibility, Including Artificial Intelligence (2024 AI SME Update) published in the Federal Register, 17 July 2024 and further clarified in the Reminders on Evaluating Subject Matter Eligibility of claims under 35 U.S.C. 101 guidance memorandum published 4 August 2025. Claim(s) 1-5, 7-13, 15-16, and 21-26 as a whole is/are determined to be directed to an abstract idea. The rationale for this determination is explained below:
Abstract ideas are excluded from patent eligibility based on a concern that monopolization of the basic tools of scientific and technological work might serve to impede, rather than promote, innovation. Still, inventions that integrate the building blocks of human ingenuity into something more by applying the abstract idea in a meaningful way are patent eligible (See MPEP 2106.04).
Consistent with the findings of the Supreme Court in Mayo Collaborative Services v. Prometheus Labs., Incorporated and Alice Corporation Pty. Ltd. v. CLS Bank International, et al. ineligible abstract ideas are defined in groups, namely: (1) Mathematical Concepts (e.g., mathematical relationships, mathematical formulas or equations, and mathematical calculations; (2) Mental Processes (e.g., concepts performed or performable in the human mind including observations, evaluations, judgements, or opinions); and (3) Certain Methods of Organizing Human Activity. Groupings of Certain Methods of Organizing Human Activity include three sub-categories within the group, namely: (1) fundamental economic principles or practices; (2) commercial or legal interactions (e.g., agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors, and business relations); (3) managing personal behavior or relationships or interactions between people (e.g., social activities, teaching, and following rules or instructions) (See MPEP 2106.04(a).
Eligibility Step 1: Four Categories of Statutory Subject Matter (See MPEP 2106.03): Independent claims 1, 9, and 21 are directed to a method, a system, and non-transitory computer-readable storage medium, respectively, and are reasonably understood to be properly directed to one of the four recognized statutory classes of invention designated by 35 U.S.C. 101; namely, a process or method, a machine or apparatus, an article of manufacture, or a composition of matter. While the claims, generally, are directed to recognized statutory classes of invention, each of method/process, system/apparatus claims, and computer-readable media/articles of manufacture are subject to additional analysis as defined by the Courts to determine whether the particularly claimed subject matter is patent-eligible with respect to these further requirements. In the case of the instant application, each of claims 1, 9, and 21 are determined to be directed to ineligible subject matter based on the following analysis/guidance:
Eligibility Step 2A prong 1: (See MPEP 2106.04): In reference to claim 1, the claimed invention is directed to non-statutory subject matter because the claim(s) as a whole, considering all claim elements both individually and in combination, do/does not amount to significantly more than an abstract idea. The claim(s) is/are directed to the abstract idea of prescribing/recommending actions to be performed during a sales process and calculating a potential reward associated with the performance of the action, which is reasonably considered to be method of Organizing Human Activity. In particular, the general subject matter to which the claims are directed is reasonably understood to be a method comprising determining and recommending optimal actions for a sales person to take in order to maximize the potential reward associated with a sales opportunity, which is an ineligible concept of Organizing Human Activity, namely: commercial interactions (e.g., marketing or sales activities or behaviors, and business relations); and managing personal behavior or interactions between people (e.g., following rules or instructions).
In support of Examiner’s conclusion, Examiner respectfully directs Applicant’s attention to the claim limitations of representative claim 1. In particular, claim 1, as presented by amendment, includes:
“…receiving...a simulated task, wherein the simulated task is associated with a plurality of attributes and a plurality of actions, wherein the plurality of actions of the simulated task includes an email message, a phone conversation, a meeting, a document sharing, a demo, a proof of concept (POC), a business valediction, a technical validation, and a contract negotiation; wherein the plurality of attributes of the simulated task includes a stage of the simulated task, and associated source contacts and target contacts of the simulated task…receiving...action information...the action information including a particular type of action and a state of the simulated task;…”, “...generating an indicator indicating whether the simulated task is associated with the type of action at the state of the simulated task... determining…a state change of the simulated task, the state change being a change in one or more attributes of the simulated task including a change in stages of the simulated task and the stages include at least a closed stage and an abandoned stage…sending…the reward and the changed state to the prescriptive agent…prescribe an action to an activity based on a current state of a task, displaying, via a graphic user interface, a current state of a task; generating…a first prescribed action when a salesperson accesses the task based on the current state of the task…wherein the first prescribed action includes an email message, a phone conversation, a meeting, a document sharing, a demo, a proof of concept (POC), a business valediction, a technical validation, a contract negotiation, or combination thereof…generating a second prescribed action when the salesperson accesses the task based on the updated state of the task…”
Considered as an ordered combination, the steps/functions of claim 1 are reasonably considered to be representative of the inventive concept and are further reasonably understood to be series of actions or activities directed to a general process of determining and recommending optimal actions for a sales person to take in order to maximize the potential reward associated with a sales opportunity, which is an ineligible concept of Organizing Human Activity, namely: commercial interactions (e.g., marketing or sales activities or behaviors, and business relations); and managing personal behavior or interactions between people (e.g., following rules or instructions) (See MPEP 2106.04(a)(2)).
Further limitations are directed to ineligible Mathematical Concepts (e.g., mathematical relationships, mathematical formulas or equations, and mathematical calculations). The courts have previously identified subject matter limited to the implementation of Mathematical Concepts as ineligible abstract ideas (See at least Gottschalk v. Benson, 409 U.S. 63, 65, 175 USPQ2d 673, 674 (1972); and Parker v. Flook, 437 U.S. 584, 588-89, 198 USPQ2d 193, 195 (1978)).
With respect to functions/steps limited to Mathematical Concepts, representative claim 1 as presented by amendment recites:
“…calculating…a reward based on the generated indicator and the state change…the step function sends the reward and the changed state to the prescriptive agent…outputs a plurality of Q scores…wherein the reward is a first predetermined value if the simulated task changes to a next stage in a life cycle of the simulated task as long as the next stage is not abandoned, wherein if the simulated task is not associated with an action, the reward is a second predetermined value, wherein if the next stage is abandoned, the reward is a third predetermined value, wherein the first predetermined value is greater than the second predetermined value and the second predetermined value is greater than the third predetermined value, wherein the ground truth value and a highest Q score of the plurality of Q scores are used to train the prescriptive agent using a loss function of the prescriptive agent…”
Considered in light of the supportive disclosure, the calculation of rewards, generation of Q-scores, and correlating reward values with lifecycle stages of tasks are understood to constitute mathematical processes applying functions to calculate/determine the recited reward values and Q-scores.
Further limitations are directed to ineligible processes/functions which are performable by Human Mental Processing and/or or by a human using pen and paper (See CyberSource Corp v. Retail Decisions, Inc., 654 F.3d 1366, 1373 (Fed. Cir. 2011). The courts have previously identified subject matter limited to steps/processes performable by Human Mental Processing and/or by a human using pen and paper to be ineligible abstract ideas (See CyberSource Corp v. Retail Decisions, Inc., 654 F.3d 1366, 1373 (Fed. Cir. 2011). Further, if a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for a recitation of generic computer components, then the claim is still to be grouped as a mental process unless the limitation cannot practically be performed in the human mind (See MPEP 2106.04(a)(2)).
With respect to functions/steps limited to processes performable by Human Mental Processing and/or by a human using pen and paper, representative claim 1, as presented by amendment, recites:
“…generating…an indicator indicating whether the simulated task is associated with the type of action at the state of the simulated task; determining…a state change of the simulated task, the state change being a change in one or more attributes of the simulated task including a change in stages of the simulated task and the stages include at least a closed stage and an abandoned stage; calculating…a reward based on the generated indicator and the state change; wherein the reward is a ground truth value to train the prescriptive agent, wherein the reward is a first predetermined value if the simulated task changes to a next stage in a life cycle of the simulated task as long as the next stage is not abandoned, wherein if the simulated task is not associated with an action, the reward is a second predetermined value, wherein if the next stage is abandoned, the reward is a third predetermined value, wherein the first predetermined value is greater than the second predetermined value and the second predetermined value is greater than the third predetermined value… prescribe an action to an activity based on a current state of a task…”
Respectfully, absent further clarification of the processing steps executed by the recited computer and platform, the above noted are performable by applying human mental processing and/or performing mathematical calculations using pen and paper. Specifically, given task information, a task state, and requisite equations, one of ordinary skill in the art would be capable of assigning or generating an indicator associated with the state, determining a change in the state, and calculating a reward based on the indicator and the state via the performance of mathematical calculations using pen and paper and/or solely employing by the human mental processing (See CyberSource Corp v. Retail Decisions, Inc., 654 F.3d 1366, 1373 (Fed. Cir. 2011) (“a method that can be performed by human thought alone is merely an abstract idea and is not patent eligible under 35 U.S.C 101).
Claims 1, 9, and 21 recite technical elements which have been considered at each step of Examiner’s analysis but are determined to constitute generic computing structures executing generic computing functions previously identified by the courts, as further analyzed under Step 2A prong 2 and Step 2B below.
Eligibility Step 2A prong 2: (See MPEP 2106.04(d)): Under step 2A prong two, Examiners are to consider additional elements recited in the claim beyond the judicial exception and evaluate whether those additional elements integrate the exception into a practical application. Further, to be considered a recitation of an element which integrates the judicial exception into a practical application, the additional elements must apply, rely on, or use the judicial exception in a manner that imposes meaningful limits on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception.
Additional technical elements of claim 1 that potentially integrate the claimed ineligible subject matter into a practical application of the claimed subject are limited to: “training platform”, “environment in training platform”, “one or more processors”, “deep neural network”, “prescriptive agent”, and “graphic user interface”. Claim 1 further indicates, generally, that the claimed method is “computer-implemented” as designated in the preamble. Claim 9 and 21, directed to a system and computer-readable medium introduce processor-executable “instructions” as engaged in a general manner in the performance of each of the recited steps/functions. With respect to these potential additional elements:
(1) The “one or more processors”, “training platform”, and “instructions” are identified as engaged in an unspecified, general manner in the performance of each of the recited steps/functions.
(2) The “environment in training platform” is identified as receiving action information.
(3) The “deep neural network” is identified as being included in the prescriptive agent.
(4) The “prescriptive agent” is identified as being trained to prescribe sales actions based on task state(s) using Q-scoring. As presented by amendment, the trained prescriptive agent is identified as prescribed action based on iterative state of the agent.
(5) The “graphic user interface” as presented by amendment is identified as displaying tasks and prescribed actions and being updated with prescribed actions and task state changes when new actions are generated and task states change.
With respect to the above noted functions attributable to the identified additional elements, MPEP 2106.05 stipulates that: Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f); Adding insignificant extra-solution activity to the judicial exception – see MPEP 2106.05(g); and/or Generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h) serve as indications that the use of the technology recited does not indicate integration into a practical application of the judicial exception.
With respect to the machine-learning prescriptive agent, claim 1 includes “…wherein the prescriptive agent includes a deep neural network which takes a state of one or more simulated tasks as an input, and outputs a plurality of Q scores, and training the prescriptive agent updates neural network values of the deep neural network using a deep reinforcement learning methodology…” and limitations specifying that the ground truth, highest Q score, and loss function are “used to train” the “prescriptive agent/deep neural network”. As presented by amendment, claim 1 specifies that first and second iterative state of the agent generate first and second prescribed actions which are displayed on the interface. With respect to these elements, Examiner directs Applicant’s attention to the 2024 Guidance Update on Patent Subject Matter Eligibility, Including Artificial Intelligence (2024 AI SME Update) published in the Federal Register on 17 July 2024.
In particular, Examiner respectfully directs Applicant’s attention to Example 47, claim 2. Specifically, the instant recitations of “using a deep reinforcement learning methodology” and “training the prescriptive agent” are analogous to the training of an artificial neural network based on input data and receiving continuous training data of Examiner 47. Reasonably, the reward and changed state are limited to mere data gathering and generating an output at a high level of generality and, by extension, are reasonably understood to constitute insignificant extra solution activity (See MPEP 2106.05(g)). While the claims states, generally, that values are updated “using a deep reinforcement learning methodology”, the recited training process is limited to a recitation of the inputs and outputs, i.e., “state” and “Q scores” to be used in training the network absent any technical specificity regarding actual training. In other words, the claim is limited to recitation of inputs and outputs, i.e., a result, but fails to specify any technical steps other than the general indication that the network is updated using a methodology.
NOTE: For Applicant’s benefit, Examiner notes that the present limitations display prescribed tasks on a user interface and retrieve or generate an action when a user “accesses” a task. As presented, the functions performed by and through the recited interface are limited to retrieval of stored information (e.g., actions) generated by versions/states of the prescriptive agents and displays the actions on a generic display. Examiner notes that amendments to clarify an iterative and dynamic configuration of the claimed interface, beyond simply updating tasks that can be accessed based on versions of the agent, but rather to generate actionable elements on the interface based on a current instance of the agent and a current state of a task could serve to overcome the maintained rejection under 35 U.S.C. 101. Further, Examiner suggests a review of paragraphs [0045]-[0048] of the Specification as originally filed with attention to the generation of action-state pairs associated with the output Q-scores. As presented, the claims merely indicate that Q-scores are outputted, but the scores are not tied to actions nor does the claim provide any indication of how the Q-scoring related to training based on actions and/or provide selective mechanisms with respect to actions associated with task state. In other words, as presented, the Q-score are merely mathematical outputs without any connection to the associated actions. Amendments to clarify this relationship could also assist in overcoming the maintained rejection under 35 U.S.C. 101.
Each of the limitations of claim 1 states a result (e.g., tasks and action information are received, an indicator is generated, and change is determined, and a reward is calculated, Q scores are generated and functions are used to receive information and train a model/agent etc.) as associated with a respective “platform” or “environment” or is performed “by a processor”. As presented by amendment, prescribed actions from iterative states of the agent are displayed. Beyond the general statement that the method is computer-implemented, the limitations provide no further clarification with respect to the functions performed by the “platform”, “environment”, or “processor” in producing the claimed result(s). A recitation of “by a processor” or “at a platform” or “at an environment”, absent clarification of particular processing steps executed by the underlying technology to produce the result are reasonably understood to constitute a general linking of the claimed process to a technical environment. The identified functions performed by the recited technology are limited to: (1) receiving and sending data via a computer network (e.g., tasks, action information, reward values and state change information); (2) storing and retrieving information and data from a generic computer memory (e.g., actions/tasks and values); (3) displaying data on a generic computer display (e.g., prescribed actions); and (4) performing repetitive calculations and/or mental observations using the obtaining information/data (e.g., calculating reward values and Q-scores, generating an indicator, determining a state change etc.) (See MPEP 2106.05(f)).
Claim 1 is reasonably understood to be conducting standard, and formally manually performed process of determining and recommending optimal actions for a sales person at a point is a sales process using the generic devices as tools to perform the abstract idea. The identified functions of the recited additional elements reasonably constitute a general linking of the abstract idea to a generic technological environment, e.g., generic devices capable of storing and retrieving information from computer memory and transmitting information over a computer network. The claimed determining and recommending optimal actions for a sales person at a point is a sales process benefits from the inherent efficiencies gained by data transmission, data storage, and information display capacities of generic computing devices, but fails to present an additional element(s) which practical integrates the judicial exception into a practical application of the judicial exception.
Eligibility Step 2B: (See MPEP 2106.05): Analysis under step 2B is further subject to the Revised Examination Procedure responsive to the Subject Matter Eligibility Decision in Berkheimer v. HP, Inc. issued by the United States Patent and Trademark Office (19 April 2018). Examiner respectfully submits that the recited uses of the underlying computer technology constitute well-known, routine, and conventional uses of generic computers operating in a network environment. In support of Examiner’s conclusion that the recited functions/role of the computer as presented in the present form of the claims constitutes known and conventional uses of generic computing technology, Examiner provides the following:
In reference to the Specification as originally filed, Examiner notes paragraphs [0057]-[0072]. In the noted disclosure, the Specification provides listings of generic computing systems, e.g., a general computing platform including exemplary servers, network configurations and various processor configuration which are identified as capable and interchangeable for performing the disclosed processes. The disclosure does not identify any particular modifications to the underlying hardware elements required to perform the inventive methods and functions. Accordingly, it is reasonably understood that this disclosure indicates that the hardware elements and network configurations suitable for performing the inventive methods are limited to commercially available systems at the time of the invention. Absent further clarification, it is reasonably understood that any modifications/improvements to the underlying technology attributable to the inventive method/system are limited to improvements realized by the disclosed computer-executable routines and the associated processes performed.
While the above noted disclosure serves to provide sufficient explanation of technical elements required to perform the inventive method using available computing technology, the disclosure does not appear to identify any particular modifications or inventive configurations of the underlying hardware elements required to perform the inventive methods and functions.
Accordingly, it is reasonably understood that the disclosure indicates that the hardware elements and network configurations suitable for performing the inventive methods are limited to commercially available systems at the time of the invention. Further, absent further clarification, it is reasonably understood that any modifications/improvements to the underlying technology attributable to the inventive method/system are limited to improvements realized by the disclosed computer-executable routines and the associated processes performed.
The claims specify that the above identified generic computing structures and associated functions/routines include:
(1) The “one or more processors”, “training platform”, and “instructions” are identified as engaged in an unspecified, general manner in the performance of each of the recited steps/functions.
(2) The “environment in training platform” is identified as receiving action information.
(3) The “deep neural network” is identified as being included in the prescriptive agent.
(4) The “prescriptive agent” is identified as being trained to prescribe sales actions based on task state(s) using Q-scoring. As presented by amendment, the trained prescriptive agent is identified as prescribed action based on iterative state of the agent.
(5) The “graphic user interface” as presented by amendment is identified as displaying tasks and prescribed actions and being updated with prescribed actions and task state changes when new actions are generated and task states change.
While Examiner acknowledges that the noted limitations are computer-implemented, Examiner respectfully submits that, in aggregate (e.g., “as a whole”) they do not amount to significantly more than the abstract idea/ineligible subject matter to which the claimed invention is primarily directed.
While utilizing a computer, the claimed invention is not rooted in computer technology nor does it improve the performance of the underlying computer technology. The computer-implemented features of the claimed invention noted above are reasonably limited to: (1) receiving and sending data via a computer network (e.g., tasks, action information, reward values and state change information); (2) storing and retrieving information and data from a generic computer memory (e.g., actions/tasks and values); (3) displaying data on a generic computer display (e.g., prescribed actions); and (4) performing repetitive calculations and/or mental observations using the obtaining information/data (e.g., calculating reward values and Q-scores, generating an indicator, determining a state change etc.).
The above listed computer-implemented functions are distinguished from the generic data storage, retrieval, transmission, and data manipulation/processing capacities of the generic systems identified in the Specification solely by the recited identification of particular data elements that are of utility to a user performing the specific method of determining and recommending optimal actions for a sales person at a point is a sales process. In summary, the computer of the instant invention is facilitating non-technical aims, i.e., determining and recommending optimal actions for a sales person at a point is a sales process, because it has been programmed to store, retrieve, and transmit specific data elements and/or instructions that is/are of utility to the user. The non-technical functions of determining and recommending optimal actions for a sales person at a point is a sales process benefit from the use of computer technology, but fail to improve the underlying technology.
In support, the courts have previously found that utilization of a computer to receive or transmit data and communications over a network and/or employing generic computer memory and processor capacities store and retrieve information from a computer memory are insufficient computer-implemented functions to establish that an otherwise unpatentable judicial exception (e.g. abstract idea) is patent eligible. With respect to the determinations of the Courts regarding using a computer for sending and receiving data or information over a computer network and storing and retrieving information from computer memory, see at least: receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362; sending messages over a network OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); receiving and sending information over a network buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); 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 and see performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199; and Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) with respect to the performance of repetitive calculations does not impose meaningful limits on the scope of the claims.
Independent claims 9 and 21, directed to an apparatus/system and computer-executable instructions stored on computer-readable media for performing the method steps are rejected for substantially the same reasons, in that the generically recited computer components in the apparatus/system and computer readable media claims add nothing of substance to the underlying abstract idea.
Dependent claims 4-5 and 12-13 as amended further include recitations indicating that the “highest Q score in an expected value” and that a “mean squared error loss function” is used to train the prescriptive agent. While these limitations clarify the nature of the Q scores and further introduce an additional “function”, the noted clarification and introduce function are limited to further clarification of the mathematics applied to the calculation of values and training of the models using defined mathematical functions. These elements fail to introduce an integrating technical element as they are limited to further definition of mathematical processes
Dependent claims 2-5, 7-8, 10-13, 15-16, and 22-26, when analyzed as a whole are held to be ineligible subject matter and are rejected under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claimed invention is not directed to an abstract idea.
Viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
In accordance with all relevant considerations and aligned with previous findings of the courts, the technical elements imparted on the method that would potentially provide a basis for meeting a “significantly more” threshold for establishing patent eligibility for an otherwise abstract concept by the use of computer technology fail to amount to significantly more than the abstract idea itself. For further guidance and authority, see Alice Corporation Pty. Ltd. v. CLS Bank International, et al. 573 U.S.____ (2014)) (See MPEP 2106).
Allowable Subject Matter
[5] Claims 1-5, 7-13, 15-16, 21-26 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action.
The most closely applicable prior art of record is referred to in the Office Action mailed 3 February 2023 as McCord et al. (United States Patent Application Publication No. 2017/0255945). As noted by Applicant in the remarks filed 13 April 2023, McCord et al. fail to teach at least:
“…receiving...a simulated task, wherein the simulated task is associated with a plurality of attributes and a plurality of actions; and training the prescriptive agent iteratively at the training platform for the simulated task …”, “…receiving...action information...the action information including a particular type of action and a state of the simulated task;…”, “...generating an indicator indicating whether the simulated task is associated with the type of action at the state of the simulated task...”, “...determining…a change in the state of the simulated task, the state change being a change in one or more attributes of the simulated task including a change in stages of the simulated task and the stages include at least a closed stage and an abandoned stage;...”, and “…and sending…the reward and the changed state to the prescriptive agent and training the prescriptive agent using the reward and the changed state, wherein the prescriptive agent includes a deep neural network which takes a state of one or more simulated tasks as an input, and outputs a plurality of Q scores, and training the prescriptive agent updates neural network values of the deep neural network using a deep reinforcement learning methodology, wherein the reward is a first predetermined value if the simulated task changes to a next stage in a life cycle of the simulated task as long as the next stage is not abandoned, wherein if the simulated task is not associated with an action, the reward is a second predetermined value, and wherein if the next stage is abandoned, the reward is a third predetermined value, wherein the first predetermined value is greater than the second predetermined value and the second predetermined value is greater than the third predetermined value…” as required by each of claims 1, 9, and 21.
Response to Remarks/Amendment
[6] Applicant's remarks filed 10 February 2026 have been fully considered and are addressed as follows:
[i] Applicant’s remarks in response to previous rejection(s) of claim(s) 1-5, 7-13, 15-16, and 21-26 under 35 U.S.C. 101 as being directed to non-statutory subject matter as set forth in the previous Office Action mailed 12 November 2025 are reasonably considered to have been fully addressed in the context of the revised rejection of the claims presented above responsive to the amendments to the subject claims and in consideration of the framework for determining patent subject matter eligibility under 35 U.S.C. 101 established in the decisions of the Supreme Court in Mayo Collaborative Services v. Prometheus Labs., Incorporated and Alice Corporation Pty. Ltd. v. CLS Bank International, et al. (See MPEP 2106 subsection III and 2106.03-2106.05) and the 2024 Guidance Update on Patent Subject Matter Eligibility, Including Artificial Intelligence (2024 AI SME Update), published in the Federal Register, 17 July 2024. Additionally, Applicant substantially rehashes arguments previously presented in the prior response. These arguments are addressed in accordance with Examiner’s response in the prior Office Action(s) mailed 12 November 2025, 24 April 2025, and 25 October 2024, incorporated in their entirety in response.
NOTE: For Applicant’s benefit, Examiner notes that the present limitations display prescribed tasks on a user interface and retrieve or generate an action when a user “accesses” a task. As presented, the functions performed by and through the recited interface are limited to retrieval of stored information (e.g., actions) generated by versions/states of the prescriptive agents and displays the actions on a generic display. Examiner notes that amendments to clarify an iterative and dynamic configuration of the claimed interface, beyond simply updating tasks that can be accessed based on versions of the agent, but rather to generate actionable elements on the interface based on a current instance of the agent and a current state of a task could serve to overcome the maintained rejection under 35 U.S.C. 101. Further, Examiner suggests a review of paragraphs [0045]-[0048] of the Specification as originally filed with attention to the generation of action-state pairs associated with the output Q-scores. As presented, the claims merely indicate that Q-scores are outputted, but the scores are not tied to actions nor does the claim provide any indication of how the Q-scoring related to training based on actions and/or provide selective mechanisms with respect to actions associated with task state. In other words, as presented, the Q-score are merely mathematical outputs without any connection to the associated actions. Amendments to clarify this relationship could also assist in overcoming the maintained rejection under 35 U.S.C. 101.
Conclusion
[7] The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Cited NON-PATENT Literature:
De Silva et al., Intelligent Agent to Negotiate on Goal Oriented Conversations, 2020-03-06, 2020 International Conference on Image Processing and Robotics (ICIP) (2020, Page(s): 1-6): Relevant Teachings: De Silva discloses a system/method that provides training and applications for an intelligent agent. The publication establishes that at least training of an intelligent (AI) agent for business negotiations using utility functions and a reward policy is common practice in the art.
Cited PATENT Literature:
Dahlmeier et al., MACHINE LEARNING FRAMEWORK FOR FACILITATING ENGAGEMENTS, United States Patent Application Publication No. 2018/0260693, paragraphs [0037]-[0041]: Relevant Teachings: Dahlmeier discloses a system/method that includes steps/functions that utilize machine learning to monitor communications between parties and recommend actions to be taken to advance a sales process based on the monitored communications/interactions.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ROBERT D RINES whose telephone number is (571)272-5585. The examiner can normally be reached M-F 9am - 5pm.
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/ROBERT D RINES/Primary Examiner, Art Unit 3625
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