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 .
Claims 1-20 are pending.
Specification
The disclosure is objected to because it contains an embedded hyperlink and/or other form of browser-executable code. Applicant is required to delete the embedded hyperlink and/or other form of browser-executable code; references to websites should be limited to the top-level domain name without any prefix such as http:// or other browser-executable code. See MPEP § 608.01.
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.
Claim 16 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the media is not excluding transitory media.
Claims 1-20 are rejected under 35 U.S.C. 101 for being directed to an abstract idea.
Claim 1 is drawn to method, which falls under a statutory category of invention under Step 1 of the 2019 Revised Patent Subject Matter Eligibility Guidance for evaluating claims for eligibility under 35 U.S.C. 101.
Claim 1 is rejected under 35 U.S.C. 101 Step 2A Prong 1 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s):
The limitation of training a neural network with a plurality of training data pairs, wherein each training data pair includes an input data processed by the solver to generate a solution of the same training data pair, as drafted, is a process that, under its broadest reasonable interpretation, is recited at a high level of generality such that they could practically be performed in the human mind and/or using mathematical concepts but for the recitation of generic computer components. But for the neural network, the recited limitation encompasses the user performing mental calculations and/or applying mathematical concepts to generate a solution using a mathematical process.
The limitation of inputting a new input data into the neural network, as drafted, does not integrate the judicial exception into a practical application as it is directed towards receiving or transmitting data over a network, which is a form of insignificant extra-solution activity. See MPEP §2106.05(d)(II)(i).
The limitation of exercising the neural network to generate a partial solution, as drafted, is a process that, under its broadest reasonable interpretation, is recited at a high level of generality such that they could practically be performed in the human mind and/or using mathematical concepts but for the recitation of generic computer components. But for the neural network, the recited limitation encompasses the user performing mental calculations and/or applying mathematical concepts to generate a solution using a mathematical process.
The limitation of applying the new input data and the partial solution to the solver, where the solution space of the solver is reduced, as drafted, is a process that, under its broadest reasonable interpretation, is recited at a high level of generality such that they could practically be performed in the human mind and/or using mathematical concepts but for the recitation of generic computer components. But for the neural network, the recited limitation encompasses the user performing mental calculations and/or applying mathematical concepts to generate a new solution with a reduced solution space using a mathematical process.
The limitation of exercising the solver to generate a new solution, wherein the solver generates the new solution more rapidly than the solver would have generated a solution without the reduction of the solution space of the solver, as drafted, is a process that, under its broadest reasonable interpretation, is recited at a high level of generality such that they could practically be performed in the human mind and/or using mathematical concepts but for the recitation of generic computer components. But for the neural network, the recited limitation encompasses the user performing mental calculations and/or applying mathematical concepts to generate a solution more rapidly by using a reduction of solution space using a mathematical process.
This judicial exception is not integrated into a practical application because the additional element(s) (i.e. neural network, computing system, mathematical programming solver, etc.) is/are recited at a high level of generality (i.e., as a generic computer software program performing a generic computer function identifying and determining values) such that they amount no more than mere instructions to apply the exception in a broad and non-specific manner that the claim as a whole is no more than a drafting effort designed to monopolize the exception. Accordingly, there is no additional element that would integrate the abstract idea into a practical application because the limitations as written do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea .
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, any well understood and generic additional elements (such as processors, generic computers, neural networks, and the like) to perform the described limitations amounts 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. The claim is not patent eligible.
Regarding claims 2-7, 14-15, 17, the additional limitations, as drafted, each relate to performance of behavior planning that merely elaborates on the abstract idea performed. Thus these claims each recite an abstract idea for the same reasons given for claim 1.
Regarding claims 8-13, 18-20, the additional limitations, as drafted, is directed towards the types of data used that is merely indicating a field of use or technological environment in which to apply a judicial exception. See 2106.05(h). Thus these claims each recite an abstract idea for the same reasons given for claim 1.
Claim 16 is drawn to a system, which falls under a statutory category of invention under Step 1 of the 2019 Revised Patent Subject Matter Eligibility Guidance for evaluating claims for eligibility under 35 U.S.C. 101.
Claim 16 is rejected under 35 U.S.C. 101 Step 2A Prong 1 because the claimed invention is directed to an abstract idea without significantly more for the same reasons as give for claim 1.
Allowable Subject Matter
Claims 1 and 16 would be allowable if rewritten or amended to overcome the rejections(s) under 35 USC 101 as set forth in this office action.
Dependent claims 2-15 and 17-20 are allowable over art based on their dependence upon claims 1 and 16 respectively.
The following is a statement of reasons for the indication of allowable subject matter: Applicant’s claim defines over the prior art of record because the prior art of record, taken either alone or in combination, does not teach training a neural network with a plurality of training data pairs, wherein each training data pair includes an input data processed by the solver to generate a solution of the same training data pair; inputting a new input data into the neural network; exercising the neural network to generate a partial solution; applying the new input data and the partial solution to the solver, where the solution space of the solver is reduced; and exercising the solver to generate a new solution, wherein the solver generates the new solution more rapidly than the solver would have generated a solution without the reduction of the solution space of the solver.
Citation of Pertinent Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Verbraeken et al, "A Survey on Distributed Machine Learning", March 2020, ACM Computing Surveys Vol 53, PP 1-33 relates to claims regarding Machine Learning (ML) algorithms being used to analyze datasets.
Nakazato, German Patent Num DE102021212483A1 relates to claims regarding a neural network that executes learning processing for updating a parameter using training data that are pairs of input data associated in advance, derive the optimal solution, and reduce the influence of the input data on the calculation of the optimal solution.
Jezewski, US Patent Pub US 20220374793 relates to claims regarding a neural network operation for reducing the solution space, input pairs, and training data sets.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVID E OGG whose telephone number is (469) 295-9163. The examiner can normally be reached on Mon - Thurs 7:30 am - 5:00 pm CT.
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/DAVID EARL OGG/
Primary Examiner, Art Unit 2119