DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This action is responsive to the Amendment filed on 01/07/2026. Claims 1, 3-5, 7, 8, 10-12, 14, 15, 17-19, and 21 are pending in the case. Claims 2, 6, 9, 13, 16, and 20 have been cancelled. Claims 1, 8, and 15 are independent claims.
Response to Arguments
Applicant's arguments regarding the 35 U.S.C. § 101 rejections of the claims have been fully considered but they are not persuasive.
Applicant argues that the newly amended limitations cannot be practically performed in the human mind (page 9). Specifically, Applicant points to the “executing a reinforcement learning module to generate a second solution, “ as not being able to be performed in the human mind (page 10). However, this step is handled as an “apply it” step under 2A Prong 2 and 2B. Essentially, the step is recited at such a high level – merely executing a reinforcement module – as to render the limitation as an apply it step.
Applicant further argues that the “comparing, by the reinforcement learning module, the first solution and the second solution,” are again unable to be performed in the human mind (page 10). However, the “by the reinforcement learning module,” is merely an apply it step and the comparison between solutions can be performed in the mind.
Applicant also points to the other executing steps as not being able to practically be performed in the human mind (page 10). These limitations too are recited in such a high level way as to render them as “apply it” steps.
Lastly, Applicant argues that the recited claim is necessarily rooted in computer technology in order to overcome a problem specifically arising in the realm of optimization services (page 11). While the Applicant may have certainly come across such a solution, the claims as they now stand are recited in such a way – in a high level way – that the rejections under 101 are not overcome.
Applicant's amendments to the claims and prior art arguments are persuasive. Accordingly, these rejections are hereby withdrawn.
Claim Rejections - 35 U.S.C. § 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, 3-5, 7, 8, 10-12, 14, 15, 17-19, and 21 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Claims 1, 3-5, and 7 are directed towards the statutory category of a process. Claims 8, 10-12, and 14 are directed towards the statutory category of a machine. Claims 15, 17-19, and 21 are directed towards the statutory category of an article of manufacture.
With respect to claim 1:
2A Prong 1: This claim is directed to a judicial exception.
A method, comprising (mental process):…
extracting a problem and use case characteristics from the payload (mental process);
predicting that at least one of a mathematical solver or a simulation optimization model capable of solving the problem having the use case characteristics (mental process);…
comparing… the first solution and the second solution for a metric to determine an optimal solution (mental process).
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
receiving, at a data processing system, a payload including a request for optimizing a service (adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g));
processing, by the data processing system, the payload, using a meta learning classifier, the processing comprising: executing the at least one machine learning model to solve the problem (merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f));
executing, based on the prediction, at least one of the mathematical solver or the simulation optimization model to generate a first solution to the problem (merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f)) – high level execution of machine learning;
executing a reinforcement learning module to generate a second solution to the problem (merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f) – high level execution of machine learning);
outputting, by the data processing system, the first solution to the problem for optimizing the service (adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g));
… by the reinforcement learning module… (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f) – high level execution of machine learning); and
providing, by the data processing system, the optimal solution to a computing device (adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g)).
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
receiving, at a data processing system, a payload including a request for optimizing a service (MPEP 2106.05(d) indicates that merely “storing and retrieving information in memory” and/or "receiving or transmitting data over a network" are well‐understood, routine, conventional functions when they are claimed in a merely generic manner (as it is in the present claim). Thereby, a conclusion that the claimed step is well-understood, routine, conventional activity is supported under Berkheimer);
processing, by the data processing system, the payload, using a meta learning classifier, the processing comprising: executing the at least one machine learning model to solve the problem (merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f));
executing, based on the prediction, at least one of the mathematical solver or the simulation optimization model to generate a first solution to the problem (merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f)) – high level execution of machine learning;
executing a reinforcement learning module to generate a second solution to the problem (merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f) – high level execution of machine learning);
outputting, by the data processing system, the first solution to the problem for optimizing the service (MPEP 2106.05(d) indicates that merely “storing and retrieving information in memory” and/or "receiving or transmitting data over a network" are well‐understood, routine, conventional functions when they are claimed in a merely generic manner (as it is in the present claim). Thereby, a conclusion that the claimed step is well-understood, routine, conventional activity is supported under Berkheimer); and
… by the reinforcement learning module… (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f) – high level execution of machine learning); and
providing, by the data processing system, the optimal solution to a computing device (MPEP 2106.05(d) indicates that merely “storing and retrieving information in memory” and/or "receiving or transmitting data over a network" are well‐understood, routine, conventional functions when they are claimed in a merely generic manner (as it is in the present claim). Thereby, a conclusion that the claimed step is well-understood, routine, conventional activity is supported under Berkheimer).
With respect to claim 3:
2A Prong 1: This claim is directed to a judicial exception.
the mathematical solver includes programs capable of solving a combination of a linear programming (LP), non-linear programming (NPL), and mixed integer programming (MIP) (mental process and/or mathematical concept);
the simulation optimization model includes programs capable of performing stochastic programming, a Monte Carlo simulation, and a discrete event simulation (mental process and/or mathematical concept); and
the reinforcement learning model includes a neural network or a deep learning model (mental process and/or mathematical concept).
2A Prong 2: This judicial exception is not integrated into a practical application.
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claim 4:
2A Prong 1: This claim is directed to a judicial exception.
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
storing all solutions created by the mathematical solver and all simulation results created by the reinforcement learning model (adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g)).
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
storing all solutions created by the mathematical solver and all simulation results created by the reinforcement learning model (MPEP 2106.05(d) indicates that merely “storing and retrieving information in memory” and/or "receiving or transmitting data over a network" are well‐understood, routine, conventional functions when they are claimed in a merely generic manner (as it is in the present claim). Thereby, a conclusion that the claimed step is well-understood, routine, conventional activity is supported under Berkheimer).
With respect to claim 5:
2A Prong 1: This claim is directed to a judicial exception.
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
reinforcement learning model is trained using the stored solutions created by the mathematical solver and the simulation optimization model (merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f) – high level recitation of machine learning).
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
reinforcement learning model is trained using the stored solutions created by the mathematical solver and the simulation optimization model (merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f) – high level recitation of machine learning).
With respect to claim 7:
2A Prong 1: This claim is directed to a judicial exception.
the predicting comprises determining whether the use case characteristics indicates that the problem is deterministic or stochastic (mental process).
2A Prong 2: This judicial exception is not integrated into a practical application.
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
The remaining claims 8, 10-12, 14, 15, 17-19, and 21 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more for at least the same reasons as those given above with respect to claims 1, 3-5, and 7 with only the addition of generic computer components under step 2A prong 1. Under the broadest reasonable interpretation, these limitations are process steps that cover mental processes including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper but for the recitation of a generic computer component. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the "Mental Process" grouping of abstract ideas. A person would readily be able to perform this process either mentally or with the assistance of pen and paper. See MPEP § 2106.04(a)(2). Limitations that merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f). These additional elements do not integrate the judicial exception into a practical application under step 2A prong 2. Refer to MPEP §2106.04(d). Moreover, the limitations are merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f). These additional elements do not recite any additional elements/limitations that amount to significantly more. Accordingly, the claimed invention recites an abstract idea without significantly more.
Conclusion
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 nonprovisional extension fee (37 CFR 1.17(a)) 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Casey R. Garner whose telephone number is 571-272-2467. The examiner can normally be reached Monday to Friday, 8am to 5pm, Eastern Time.
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/Casey R. Garner/Primary Examiner, Art Unit 2123