DETAILED ACTION
This action is in response to the Applicant Response filed 16 March 2026 for application 18/114,197 filed 24 February 2023.
Claim(s) 1, 3-4, 10, 12-13, 19 is/are currently amended.
Claim(s) 21-23 is/are new.
Claim(s) 2, 11, 20 is/are cancelled.
Claim(s) 1, 3-10, 12-19, 21-23 is/are pending.
Claim(s) 1, 3-10, 12-19, 21-23 is/are rejected.
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 .
Response to Arguments
Applicant's arguments regarding the 35 U.S.C. 112(b) rejection(s) of claim(s) 4-5, 13-14 have been fully considered and, in light of the amendments to the claims, are persuasive. The 35 U.S.C. 112(b) rejection(s) of claim(s) 4-5, 13-14 has/have been withdrawn.
Applicant’s arguments regarding the 35 U.S.C. 101 rejection of claims 1, 3-10, 12-19, 21-23 have been fully considered but are not persuasive.
Applicant first argues that in light of Desjardins, the claim is eligible. Examiner respectfully disagrees. Desjardins includes an improvement related to catastrophic forgetting while the claims in the instant application only recite machine learning at a high level to perform an abstract idea, as detailed below. While Desjardins provides a specific training strategy that allows models to preserve performance on earlier tasks even as it learns new ones, the current claims merely employ generic machine learning at a high level to perform feature extraction and classification as part of a generic reinforcement learning procedure.
Applicant next argues that in light of the July 2024 guidance and the August 2025 memo that the claims should be eligible as they recite AI-related limitations. Examiner respectfully disagrees, as this is a misinterpretation of the guidance. There is no guidance issued by the Office that states that any field of technology is automatically eligible. The MPEP lays out a step-by-step analysis for eligibility. This analysis is not changed by any additional guidance issued by the Office. Any additional guidance is issued to provide clarity to the analysis, but the analysis must still be performed as directed by the MPEP. As detailed below, the analysis was performed on the claims and the claims were found to be ineligible. Examiner also notes that the Office release several AI-related SME examples (Examples 47-49) to assist with the analysis of AI-related technologies.
Applicant next argues that the claims provide a particular solution to a particular problem. Examiner respectfully disagrees. As currently recited, claim 1 simply recites a generic reinforcement learning process which includes feature extraction and classification. The claims fail to recite any particular limitations that would lead Examiner to identify a particular solution to a particular problem.
Therefore, the 35 U.S.C. 103 rejection of claims 1, 3-10, 12-19, 21-23 is maintained.
Applicant’s arguments regarding the 35 U.S.C. 103 rejections of claims 1, 3-10, 12-19, 21-23 have been fully considered but are not persuasive.
Applicant first argues that the Office Action appears to use Rawat as an anticipation-type rejection although it is described as a single reference obviousness-type rejection and there is no discussion as to what is inferred versus expressly disclosed, and the rejection is therefore improper. Examiner respectfully disagrees. First there is no appearance of an anticipation-type rejection. There is no mention in the Office Action of anticipation and the header for the rejection and the cited statues are fora 35 U.S.C. 103 obviousness rejection. Moreover, the mapping to Rawat for the limitation execute a reinforcement learning process on at least a portion of the obtained information to determine one or more parameters provides applicant with sufficient detail to determine what is expressly recited versus what is obvious. The reference states that the meta-model process a portion of the information to determine parameters (Rawat, [0025]). However, Rawat does not expressly recite a reinforcement learning process determining the parameters. Rawat does, however, further teach that the meta-model includes one or more models configured to use reinforcement learning (Rawat, [0035]). Therefore, the Office action provided the mappings to show an obviousness rejection for the limitations while demonstrating that the reference dis not expressly recite the limitation. See MPEP 2144.08.
Applicant next argues that the cited reference fail to teach the reinforcement model determining whether the parameters are applicable to one or more specific processes or to the entirety of the processes. Examiner respectfully disagrees. Rawat teaches that the meta-model can determine hyperparameters which correspond to the entirety of the processes or the meta-model can determine process specific learning parameters (Rawat, [0041]-[0043]). Therefore, Rawat does, in fact, teach identifying to which processes the parameters apply.
Therefore claims 1, 3-10, 12-19, 21-23 stand rejected under 35 U.S.C. 103.
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(s) 1, 3-10, 12-19, 21-23 is/are rejected under 35 U.S.C. 101, because the claim(s) is/are directed to an abstract idea, and because the claim elements, whether considered individually or in combination, do not amount to significantly more than the abstract idea, see Alice Corporation Pty. Ltd. V. CLS Bank International et al., 573 US 208 (2014).
Regarding claim 1, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 1 is directed to a(n) apparatus, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) apparatus.
The limitation of obtain information from at least one of a plurality of data feature extraction and selection processes that respectively operate in conjunction with a plurality of machine learning classification processes that determine intent of data generated by execution of at least one of a plurality of applications in an information processing system, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of ... determine when the one or more parameters are applicable to one or more specific ones of the plurality of machine learning classification processes and when the one or more parameters are applicable to the entirety of the plurality of machine learning classification processes, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the "Mental Processes" grouping. Accordingly, the claim recites an abstract idea.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites additional element(s) – apparatus, at least one processing platform, at least one processor, at least one memory, program code, plurality of applications, information processing system. The additional element(s) is/are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions of executing instructions on the computers) such that it amounts to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b)).
The claim recites additional element(s) – data feature extraction and selection processes, plurality of machine learning classification processes, reinforcement learning process. The additional element(s) is/are recited at a high-level of generality such that it amounts to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h)).
The claim recites execute a reinforcement learning process on at least a portion of the obtained information to determine one or more parameters; propagate the one or more parameters to one or more of the plurality of data feature extraction and selection processes for use in training of the one or more of the plurality of data feature extraction and selection processes to respectively operate in conjunction with one or more corresponding ones of the plurality of machine learning classification processes which is simply applying a model recited at a high level of generality and amounts to the recitation of the words “apply it” (or an equivalent) or amounts to no more than mere instructions to implement an abstract idea or other exception on a computer (MPEP 2106.05(f)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the abstract idea into a practical application, the additional element(s) of:
apparatus, at least one processing platform, at least one processor, at least one memory, program code, plurality of applications, information processing system amount(s) to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b))
applying a model amount(s) to no more than mere instructions to apply the exception (MPEP 2106.05(f))
data feature extraction and selection processes, plurality of machine learning classification processes, reinforcement learning process amount(s) to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 3, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 3 is directed to a(n) apparatus, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) apparatus. The Step 2A Prong One Analysis for claim 1 is applicable here since claim 3 carries out the apparatus of claim 1 but for the recitation of additional element(s) of wherein the reinforcement learning process further comprises a Deep Recurrent Q Network (DRQN).
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites wherein the reinforcement learning process further comprises a Deep Recurrent Q Network (DRQN) which is simply additional information regarding the reinforcement learning process, and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)).
The claim recites additional element(s) – Deep Recurrent Q Network (DRQN). The additional element(s) is/are recited at a high-level of generality such that it amounts to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the abstract idea into a practical application, the additional element(s) of:
Deep Recurrent Q Network (DRQN) amount(s) to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h))
additional information regarding the reinforcement learning process do(es) not apply the exception in a meaningful way (MPEP 2106.05(e))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 4, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 4 is directed to a(n) apparatus, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) apparatus.
The limitation of ... make the applicability determination based on a determination that the one or more parameters have a given probability of improving the one or more of the machine learning classification processes or have the given probability of improving the entirety of the plurality of machine learning classification processes, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the "Mental Processes" grouping. Accordingly, the claim recites an abstract idea.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated
into a practical application. The claim does not recite any additional elements which integrate the
abstract idea into a practical application and, therefore, does not impose any meaningful limits on
practicing the abstract idea. Therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the
abstract idea into a practical application, the claim does not recite any additional elements which
provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 5, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 5 is directed to a(n) apparatus, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) apparatus. The Step 2A Prong One Analysis for claim 4 is applicable here since claim 5 carries out the apparatus of claim 4 but for the recitation of additional element(s) of wherein improvement of a given one of the machine learning classification processes comprises an improved classification inference for the given one of the machine learning classification processes.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application. In particular, the claim recites additional information regarding the machine learning classification processes and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the abstract idea into a practical application, the additional element(s) of additional information regarding the machine learning classification processes do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Not applying the exception in a meaningful way does not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 6, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 6 is directed to a(n) apparatus, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) apparatus. The Step 2A Prong One Analysis for claim 1 is applicable here since claim 6 carries out the apparatus of claim 1 but for the recitation of additional element(s) of wherein the plurality of machine learning classification processes corresponds to multiple different use cases.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application. In particular, the claim recites additional information regarding the machine learning classification processes and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the abstract idea into a practical application, the additional element(s) of additional information regarding the machine learning classification processes do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Not applying the exception in a meaningful way does not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 7, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 7 is directed to a(n) apparatus, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) apparatus. The Step 2A Prong One Analysis for claim 6 is applicable here since claim 7 carries out the apparatus of claim 6 but for the recitation of additional element(s) of wherein the at least one processing platform is configured to implement a plurality of reinforcement learning agent modules that respectively correspond to the multiple different use cases.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites wherein the at least one processing platform is configured to implement a plurality of reinforcement learning agent modules that respectively correspond to the multiple different use cases which is simply additional information regarding the t least one processing platform, and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)).
The claim recites wherein the at least one processing platform is configured to implement a plurality of reinforcement learning agent modules that respectively correspond to the multiple different use cases which is simply applying the model recited at a high level of generality and amounts to the recitation of the words “apply it” (or an equivalent) or amounts to no more than mere instructions to implement an abstract idea or other exception on a computer (MPEP 2106.05(f)).
The claim recites additional element(s) – plurality of reinforcement learning agent modules. The additional element(s) is/are recited at a high-level of generality such that it amounts to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the abstract idea into a practical application, the additional element(s) of:
applying the model amount(s) to no more than mere instructions to apply the exception (MPEP 2106.05(f))
plurality of reinforcement learning agent modules amount(s) to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h))
additional information regarding the t least one processing platform do(es) not apply the exception in a meaningful way (MPEP 2106.05(e))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 8, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 8 is directed to a(n) apparatus, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) apparatus. The Step 2A Prong One Analysis for claim 1 is applicable here since claim 8 carries out the apparatus of claim 1 but for the recitation of additional element(s) of wherein the information processing system comprises a distributed edge system.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites wherein the information processing system comprises a distributed edge system which is simply additional information regarding the information processing system, and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)).
The claim recites additional element(s) – distributed edge system. The additional element(s) is/are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions of executing instructions on the computers) such that it amounts to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the abstract idea into a practical application, the additional element(s) of:
distributed edge system amount(s) to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b))
additional information regarding the information processing system do(es) not apply the exception in a meaningful way (MPEP 2106.05(e))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 9, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 9 is directed to a(n) apparatus, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) apparatus. The Step 2A Prong One Analysis for claim 8 is applicable here since claim 9 carries out the apparatus of claim 8 but for the recitation of additional element(s) of wherein the distributed edge system is part of a multicloud edge platform.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites wherein the distributed edge system is part of a multicloud edge platform which is simply additional information regarding the distributed edge system, and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)).
The claim recites additional element(s) – multicloud edge platform. The additional element(s) is/are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions of executing instructions on the computers) such that it amounts to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the abstract idea into a practical application, the additional element(s) of:
multicloud edge platform amount(s) to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b))
additional information regarding the distributed edge system do(es) not apply the exception in a meaningful way (MPEP 2106.05(e))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 10, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 10 is directed to a(n) computer program product, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) computer program product.
The limitation of obtain information from at least one of a plurality of data feature extraction and selection processes that respectively operate in conjunction with a plurality of machine learning classification processes that determine intent of data generated by execution of at least one of a plurality of applications in an information processing system, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of ... determine when the one or more parameters are applicable to one or more specific ones of the plurality of machine learning classification processes and when the one or more parameters are applicable to the entirety of the plurality of machine learning classification processes, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the "Mental Processes" grouping. Accordingly, the claim recites an abstract idea.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites additional element(s) – computer program product, processor-readable storage medium, program code of one or more software programs, at least one processing device, plurality of applications, information processing system. The additional element(s) is/are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions of executing instructions on the computers) such that it amounts to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b)).
The claim recites additional element(s) – data feature extraction and selection processes, plurality of machine learning classification processes, reinforcement learning process. The additional element(s) is/are recited at a high-level of generality such that it amounts to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h)).
The claim recites execute a reinforcement learning process on at least a portion of the obtained information to determine one or more parameters; propagate the one or more parameters to one or more of the plurality of data feature extraction and selection processes for use in training of the one or more of the plurality of data feature extraction and selection processes to respectively operate in conjunction with one or more corresponding ones of the plurality of machine learning classification processes which is simply applying a model recited at a high level of generality and amounts to the recitation of the words “apply it” (or an equivalent) or amounts to no more than mere instructions to implement an abstract idea or other exception on a computer (MPEP 2106.05(f)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the abstract idea into a practical application, the additional element(s) of:
computer program product, processor-readable storage medium, program code of one or more software programs, at least one processing device, plurality of applications, information processing system amount(s) to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b))
applying a model amount(s) to no more than mere instructions to apply the exception (MPEP 2106.05(f))
data feature extraction and selection processes, plurality of machine learning classification processes, reinforcement learning process amount(s) to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 12, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 12 is directed to a(n) computer program product, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) computer program product. The Step 2A Prong One Analysis for claim 10 is applicable here since claim 12 carries out the computer program product of claim 10 but for the recitation of additional element(s) of wherein the reinforcement learning process further comprises a Deep Recurrent Q Network (DRQN).
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites wherein the reinforcement learning process further comprises a Deep Recurrent Q Network (DRQN) which is simply additional information regarding the reinforcement learning process, and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)).
The claim recites additional element(s) – Deep Recurrent Q Network (DRQN). The additional element(s) is/are recited at a high-level of generality such that it amounts to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the abstract idea into a practical application, the additional element(s) of:
Deep Recurrent Q Network (DRQN) amount(s) to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h))
additional information regarding the reinforcement learning process do(es) not apply the exception in a meaningful way (MPEP 2106.05(e))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 13, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 13 is directed to a(n) computer program product, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) computer program product.
The limitation of ... make the applicability determination based on a determination that the one or more parameters have a given probability of improving the one or more of the machine learning classification processes or have the given probability of improving the entirety of the plurality of machine learning classification processes, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the "Mental Processes" grouping. Accordingly, the claim recites an abstract idea.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated
into a practical application. The claim does not recite any additional elements which integrate the
abstract idea into a practical application and, therefore, does not impose any meaningful limits on
practicing the abstract idea. Therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the
abstract idea into a practical application, the claim does not recite any additional elements which
provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 14, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 14 is directed to a(n) computer program product, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) computer program product. The Step 2A Prong One Analysis for claim 13 is applicable here since claim 14 carries out the computer program product of claim 13 but for the recitation of additional element(s) of wherein improvement of a given one of the machine learning classification processes comprises an improved classification inference for the given one of the machine learning classification processes.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application. In particular, the claim recites additional information regarding the machine learning classification processes and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the abstract idea into a practical application, the additional element(s) of additional information regarding the machine learning classification processes do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Not applying the exception in a meaningful way does not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 15, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 15 is directed to a(n) computer program product, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) computer program product. The Step 2A Prong One Analysis for claim 10 is applicable here since claim 15 carries out the computer program product of claim 10 but for the recitation of additional element(s) of wherein the plurality of machine learning classification processes corresponds to multiple different use cases.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application. In particular, the claim recites additional information regarding the machine learning classification processes and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the abstract idea into a practical application, the additional element(s) of additional information regarding the machine learning classification processes do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Not applying the exception in a meaningful way does not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 16, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 16 is directed to a(n) computer program product, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) computer program product. The Step 2A Prong One Analysis for claim 15 is applicable here since claim 16 carries out the computer program product of claim 15 but for the recitation of additional element(s) of wherein the at least one processing device is configured to implement a plurality of reinforcement learning agent modules that respectively correspond to the multiple different use cases.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites wherein the at least one processing device is configured to implement a plurality of reinforcement learning agent modules that respectively correspond to the multiple different use cases which is simply additional information regarding the t least one processing platform, and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)).
The claim recites wherein the at least one processing device is configured to implement a plurality of reinforcement learning agent modules that respectively correspond to the multiple different use cases which is simply applying the model recited at a high level of generality and amounts to the recitation of the words “apply it” (or an equivalent) or amounts to no more than mere instructions to implement an abstract idea or other exception on a computer (MPEP 2106.05(f)).
The claim recites additional element(s) – plurality of reinforcement learning agent modules. The additional element(s) is/are recited at a high-level of generality such that it amounts to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the abstract idea into a practical application, the additional element(s) of:
applying the model amount(s) to no more than mere instructions to apply the exception (MPEP 2106.05(f))
plurality of reinforcement learning agent modules amount(s) to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h))
additional information regarding the t least one processing platform do(es) not apply the exception in a meaningful way (MPEP 2106.05(e))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 17, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 17 is directed to a(n) computer program product, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) computer program product. The Step 2A Prong One Analysis for claim 10 is applicable here since claim 17 carries out the computer program product of claim 10 but for the recitation of additional element(s) of wherein the information processing system comprises a distributed edge system.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites wherein the information processing system comprises a distributed edge system which is simply additional information regarding the information processing system, and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)).
The claim recites additional element(s) – distributed edge system. The additional element(s) is/are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions of executing instructions on the computers) such that it amounts to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the abstract idea into a practical application, the additional element(s) of:
distributed edge system amount(s) to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b))
additional information regarding the information processing system do(es) not apply the exception in a meaningful way (MPEP 2106.05(e))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 18, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 18 is directed to a(n) computer program product, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) computer program product. The Step 2A Prong One Analysis for claim 17 is applicable here since claim 18 carries out the computer program product of claim 17 but for the recitation of additional element(s) of wherein the distributed edge system is part of a multicloud edge platform.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites wherein the distributed edge system is part of a multicloud edge platform which is simply additional information regarding the distributed edge system, and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)).
The claim recites additional element(s) – multicloud edge platform. The additional element(s) is/are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions of executing instructions on the computers) such that it amounts to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the abstract idea into a practical application, the additional element(s) of:
multicloud edge platform amount(s) to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b))
additional information regarding the distributed edge system do(es) not apply the exception in a meaningful way (MPEP 2106.05(e))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 19, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 19 is directed to a(n) method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) method.
The limitation of obtaining information from at least one of a plurality of data feature extraction and selection processes that respectively operate in conjunction with a plurality of machine learning classification processes that determine intent of data generated by execution of at least one of a plurality of applications in an information processing system, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of ... determine when the one or more parameters are applicable to one or more specific ones of the plurality of machine learning classification processes and when the one or more parameters are applicable to the entirety of the plurality of machine learning classification processes, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the "Mental Processes" grouping. Accordingly, the claim recites an abstract idea.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites additional element(s) – processing platform, at least one processor, at least one memory, program code, plurality of applications, information processing system. The additional element(s) is/are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions of executing instructions on the computers) such that it amounts to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b)).
The claim recites additional element(s) – data feature extraction and selection processes, plurality of machine learning classification processes, reinforcement learning process. The additional element(s) is/are recited at a high-level of generality such that it amounts to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h)).
The claim recites executing a reinforcement learning process on at least a portion of the obtained information to determine one or more parameters; propagating the one or more parameters to one or more of the plurality of data feature extraction and selection processes for use in training of the one or more of the plurality of data feature extraction and selection processes to respectively operate in conjunction with one or more corresponding ones of the plurality of machine learning classification processes which is simply applying a model recited at a high level of generality and amounts to the recitation of the words “apply it” (or an equivalent) or amounts to no more than mere instructions to implement an abstract idea or other exception on a computer (MPEP 2106.05(f)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the abstract idea into a practical application, the additional element(s) of:
processing platform, at least one processor, at least one memory, program code, plurality of applications, information processing system amount(s) to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b))
applying a model amount(s) to no more than mere instructions to apply the exception (MPEP 2106.05(f))
data feature extraction and selection processes, plurality of machine learning classification processes, reinforcement learning process amount(s) to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 21, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 21 is directed to a(n) method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) method. The Step 2A Prong One Analysis for claim 19 is applicable here since claim 21 carries out the method of claim 19 but for the recitation of additional element(s) of wherein the plurality of machine learning classification processes corresponds to multiple different use cases.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application. In particular, the claim recites additional information regarding the machine learning classification processes and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the abstract idea into a practical application, the additional element(s) of additional information regarding the machine learning classification processes do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Not applying the exception in a meaningful way does not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 22, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 22 is directed to a(n) method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) method. The Step 2A Prong One Analysis for claim 21 is applicable here since claim 22 carries out the method of claim 21 but for the recitation of additional element(s) of implementing a plurality of reinforcement learning agent modules that respectively correspond to the multiple different use cases.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites implementing a plurality of reinforcement learning agent modules that respectively correspond to the multiple different use cases which is simply applying the model recited at a high level of generality and amounts to the recitation of the words “apply it” (or an equivalent) or amounts to no more than mere instructions to implement an abstract idea or other exception on a computer (MPEP 2106.05(f)).
The claim recites additional element(s) – plurality of reinforcement learning agent modules. The additional element(s) is/are recited at a high-level of generality such that it amounts to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the abstract idea into a practical application, the additional element(s) of:
applying the model amount(s) to no more than mere instructions to apply the exception (MPEP 2106.05(f))
plurality of reinforcement learning agent modules amount(s) to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 23, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 23 is directed to a(n) computer program product, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) computer program product. The Step 2A Prong One Analysis for claim 19 is applicable here since claim 23 carries out the method of claim 19 but for the recitation of additional element(s) of wherein the information processing system comprises a distributed edge system.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites wherein the information processing system comprises a distributed edge system which is simply additional information regarding the information processing system, and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)).
The claim recites additional element(s) – distributed edge system. The additional element(s) is/are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions of executing instructions on the computers) such that it amounts to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: 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 the integration of the abstract idea into a practical application, the additional element(s) of:
distributed edge system amount(s) to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b))
additional information regarding the information processing system do(es) not apply the exception in a meaningful way (MPEP 2106.05(e))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Claim Rejections - 35 USC § 103
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.
The factual inquiries 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.
Claim(s) 1, 4-10, 13-19, 21-23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rawat et al. (US 2022/0188690 A1 – Machine Learning Security Threat Detection Using a Meta-Learning Model, hereinafter referred to as “Rawat”).
Regarding claim 1 (Currently Amended), Rawat teaches an apparatus comprising:
at least one processing platform comprising at least one processor coupled to at least one memory, the at least one processing platform, when executing program code (Rawat, [0085] – teaches an execution device [processor] which executes instructions stored in memory), is configured to:
obtain information from at least one of a plurality of data feature extraction and selection processes (Rawat, [0037]-[0039] – teaches extracting features and clustering the features by action type [selection]; see also Rawat, Fig. 1) that respectively operate in conjunction with a plurality of machine learning classification processes (Rawat, [0040] – teaches that the extracted and clustered features are passed to the classification model; see also Rawat, [0021] - teaches a list of security threats; Rawat, [0026] - teaches that the classifier could be binary; Rawat, [0067]-[0073] - teaches cloud computing with multiple edge devices; see also Rawat, Fig. 1) that determine intent of data generated by execution of at least one of a plurality of applications in an information processing system (Rawat, [0022] – teaches identifying security threats in various applications using a threat detection system);
execute a reinforcement learning process on at least a portion of the obtained information to determine one or more parameters (Rawat, [0025] – teaches the meta-learning model takes in extracted features and determines learning parameters; Rawat, [0035] – teaches the meta-learning model includes one or more deep learning models using reinforcement learning; see also Rawat, Fig. 1); and
propagate the one or more parameters to one or more of the plurality of data feature extraction and selection processes for use in training of the one or more of the plurality of data feature extraction and selection processes to respectively operate in conjunction with one or more corresponding ones of the plurality of machine learning classification processes (Rawat, [0041]-[0043] – teaches the meta-learning models determining parameters for the classification and clustering [feature selection] models and transmit the updated parameters to the models; see also Rawat, Fig. 1);
wherein the reinforcement learning process is further configured to determine when the one or more parameters are applicable to one or more specific ones of the plurality of machine learning classification processes and when the one or more parameters are applicable to the entirety of the plurality of machine learning classification processes (Rawat, [0041]-[0043] – teaches the meta-learning models determining optimal parameters for the classification and clustering [feature selection] models; see also Rawat, [0021] - teaches a list of security threats; Rawat, [0026] - teaches that the classifier could be binary; Rawat, [0067]-[0073] - teaches cloud computing with multiple edge devices; Rawat, [0046]-[0047] - teaches a drift example).
Regarding claim 4 (Currently Amended), Rawat teaches all of the limitations of the apparatus of claim 1 as noted above. Rawat further teaches wherein the reinforcement learning process is further configured to make the applicability determination based on a determination that the one or more parameters have a given probability of improving the one or more of the machine learning classification processes or have the given probability of improving the entirety of the plurality of machine learning classification processes (Rawat, [0041]-[0043] – teaches the meta-learning models determining optimal parameters for the classification and clustering [feature selection] models; see also Rawat, [0021] - teaches a list of security threats; Rawat, [0026] - teaches that the classifier could be binary; Rawat, [0067]-[0073] - teaches cloud computing with multiple edge devices; Rawat, [0046]-[0047] - teaches a drift example).
Regarding claim 5 (Original), Rawat teaches all of the limitations of the apparatus of claim 4 as noted above. Rawat further teaches wherein improvement of a given one of the machine learning classification processes comprises an improved classification inference for the given one of the machine learning classification processes (Rawat, [0017] - teaches the meta-learning model generated real-time updated to ensure response to the most relevant threats and improve adaptability of threat detection [improve accuracy]; Rawat, [0041]-[0043] – teaches the meta-learning models determining optimal parameters for the classification and clustering [feature selection] models; see also Rawat, [0021] - teaches a list of security threats; Rawat, [0026] - teaches that the classifier could be binary; Rawat, [0067]-[0073] - teaches cloud computing with multiple edge devices; Rawat, [0046]-[0047] - teaches a drift example).
Regarding claim 6 (Original), Rawat teaches all of the limitations of the apparatus of claim 1 as noted above. Rawat further teaches wherein the plurality of machine learning classification processes corresponds to multiple different use cases (Rawat, [0021] - teaches a list of security threats; Rawat, [0026] - teaches that the classifier could be binary; Rawat, [0067]-[0073] - teaches cloud computing with multiple edge devices).
Regarding claim 7 (Original), Rawat teaches all of the limitations of the apparatus of claim 6 as noted above. Rawat further teaches wherein the at least one processing platform is configured to implement a plurality of reinforcement learning agent modules that respectively correspond to the multiple different use cases (Rawat, [0021] - teaches a list of security threats; Rawat, [0026] - teaches that the classifier could be binary; Rawat, [0047] - teaches different meta-learning models; Rawat, [0067]-[0073] - teaches cloud computing with multiple edge devices; see also Rawat, Fig. 4).
Regarding claim 8 (Original), Rawat teaches all of the limitations of the apparatus of claim 1 as noted above. Rawat further teaches wherein the information processing system comprises a distributed edge system (Rawat, [0067]-[0073] - teaches cloud computing with multiple edge devices; see also Rawat, Figs. 5-6).
Regarding claim 9 (Original), Rawat teaches all of the limitations of the apparatus of claim 8 as noted above. Rawat further teaches wherein the distributed edge system is part of a multicloud edge platform (Rawat, [0067]-[0073] - teaches cloud computing with multiple edge devices and one or more cloud computing nodes; see also Rawat, Figs. 5-6).
Regarding claim 10 (Currently Amended), it is the computer program product embodiment of claim 1 with similar limitations to claim 1 and is rejected using the same reasoning found in claim 1. Rawat further teaches a computer program product comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device causes the at least one processing device to (Rawat, [0085] – teaches an execution device [processor] which executes instructions stored in memory) …
Regarding claim 13 (Currently Amended), the rejection of claim 10 is incorporated herein. Further, the limitations in this claim are taught by Rawat for the reasons set forth in the rejection of claim 4.
Regarding claim 14 (Original), the rejection of claim 13 is incorporated herein. Further, the limitations in this claim are taught by Rawat for the reasons set forth in the rejection of claim 5.
Regarding claim 15 (Original), the rejection of claim 10 is incorporated herein. Further, the limitations in this claim are taught by Rawat for the reasons set forth in the rejection of claim 6.
Regarding claim 16 (Original), the rejection of claim 15 is incorporated herein. Further, the limitations in this claim are taught by Rawat for the reasons set forth in the rejection of claim 7.
Regarding claim 17 (Original), the rejection of claim 10 is incorporated herein. Further, the limitations in this claim are taught by Rawat for the reasons set forth in the rejection of claim 8.
Regarding claim 18 (Original), the rejection of claim 17 is incorporated herein. Further, the limitations in this claim are taught by Rawat for the reasons set forth in the rejection of claim 9.
Regarding claim 19 (Currently Amended), it is the method embodiment of claim 1 with similar limitations to claim 1 and is rejected using the same reasoning found in claim 1.
Regarding claim 21 (New), the rejection of claim 19 is incorporated herein. Further, the limitations in this claim are taught by Rawat for the reasons set forth in the rejection of claim 6.
Regarding claim 22 (New), the rejection of claim 21 is incorporated herein. Further, the limitations in this claim are taught by Rawat for the reasons set forth in the rejection of claim 7.
Regarding claim 23 (New), the rejection of claim 19 is incorporated herein. Further, the limitations in this claim are taught by Rawat for the reasons set forth in the rejection of claim 8.
Claim(s) 3, 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rawat in view of Hausknecht et al. (Deep Recurrent Q-Learning for Partially Observable MDPs, hereinafter referred to as “Hausknecht”).
Regarding claim 3 (Currently Amended), Rawat teaches all of the limitations of the apparatus of claim 1 as noted above. However, Rawat does not explicitly teach wherein the reinforcement learning process further comprises a Deep Recurrent Q Network (DRQN).
Hausknecht teaches wherein the reinforcement learning process further comprises a Deep Recurrent Q Network (DRQN) (Hausknecht, DRQN Architecture section – teaches using a DRQN model for reinforcement learning).
It would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to modify Rawat with the teachings of Hausknecht in order to integrate information through time to increase performance for partially observable environments in the field of reinforcement based meta-learning (Hausknecht, Abstract – “Deep Reinforcement Learning has yielded proficient controllers for complex tasks. However, these controllers have limited memory and rely on being able to perceive the complete game screen at each decision point. To address these shortcomings, this article investigates the effects of adding recurrency to a Deep Q-Network (DQN) by replacing the first post-convolutional fully-connected layer with a recurrent LSTM. The resulting Deep Recurrent Q-Network (DRQN), although capable of seeing only a single frame at each timestep, successfully integrates information through time and replicates DQN’s performance on standard Atari games and partially observed equivalents featuring flickering game screens. Additionally, when trained with partial observations and evaluated with incrementally more complete observations, DRQN’s performance scales as a function of observability. Conversely, when trained with full observations and evaluated with partial observations, DRQN’s performance degrades less than DQN’s. Thus, given the same length of history, recurrency is a viable alternative to stacking a history of frames in the DQN’s input layer and while recurrency confers no systematic advantage when learning to play the game, the recurrent net can better adapt at evaluation time if the quality of observations changes.”).
Regarding claim 12 (Currently Amended), the rejection of claim 10 is incorporated herein. Further, the limitations in this claim are taught by Rawat in view of Hausknecht for the reasons set forth in the rejection of claim 3.
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 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 communication from the examiner should be directed to MARSHALL WERNER whose telephone number is (469) 295-9143. The examiner can normally be reached on Monday – Thursday 7:30 AM – 4:30 PM ET.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kamran Afshar, can be reached at (571) 272-7796. The fax number for the organization where this application or proceeding is assigned is (571) 273-8300.
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/MARSHALL L WERNER/ Primary Examiner, Art Unit 2125