DETAILED ACTION
Notice of 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 .
Status of Claims
This action is in reply to the request for continued examination filed on December 10, 2025.
Claims 1–20 have been canceled.
Claims 21–28 have been added.
Claims 21–28 are currently pending and have been examined.
Continued Examination
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant’s submission filed on December 10, 2025 has been entered.
Response to Amendment
The amendment filed December 10, 2025 has been entered. Claims 21–28 remain pending in the application.
Claim Rejections - 35 USC § 101
The following is a quotation of 35 U.S.C. 101:
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 21–28 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
First of all, claims must be directed to one or more of the following statutory categories: a process, a machine, a manufacture, or a composition of matter. Claims 21–25 are directed to a machine (“A system”), and claims 26–28 are directed to a process (“A method”). Thus, claims 21–28 satisfy Step One because they are all within one of the four statutory categories of eligible subject matter.
Claims 21–28, however, are directed to an abstract idea without significantly more. For claim 21, the specific limitations that recite an abstract idea are:
. . . compare metadata, learned features, contextual information associated with a service request, and learnings associated . . . with the micro-AEAs, and identifying relationships, commonalities, and differences among such learned features and metadata to contribute to generating an inference corresponding to a protocol specification, and receiving learned representations . . . to support the comparative-analysis operations;
wherein the protocol specification defines a dialogue-based bilateral interaction protocol comprising steps, conditions, and sequencing of message exchanges occurring in turns between . . . agents;
wherein insight . . . is represented as an intermediate model output representing an insight, and inference generated in response to metadata corresponding to the protocol specification is represented as a computed model output representing an inference, and . . . transform the protocol specification together with the computed model output representing the inference into an executable protocol implementation;
. . . generate an invocation . . . for generating at least one protocol for the protocol specification in response to a service request received from a client . . . processing the protocol specification, and to transmit the protocol specification . . .;
. . . receive the invocation and the protocol specification, compute the intermediate model output representing the insight . . ., and transmit the intermediate model output representing the insight . . . receive the intermediate model output representing the insight and to transmit metadata corresponding to the protocol specification and the intermediate model output representing the insight and contextual information associated with the service request . . .;
. . . upon receiving the metadata, to generate the computed model output representing the inference by applying the intermediate model output representing the insight and the metadata . . . to analyze the metadata and the learnings . . . by comparing learned patterns and features . . . and identifying commonalities and differences among the learned patterns and features, generate the computed model output representing the inference based on the analysis, and transmit the computed model output representing the inference . . .; and
. . . execute the generated protocol implementation such that the action associated with the service request is performed.
Claims 21–25, therefore, recite determining protocols for executing a service request, which is the abstract idea of certain methods of organizing human activity because they recite a commercial interaction. This is further evidenced by the specification, which indicates that the service request recited in the claims relates to economic transactions and other interactions in various problem domains, including finance (U.S. Patent App. Pub. No. 2023/0297860, ¶ 110: AEAs transact with each another for wide range of economic transactions; ¶ 62: problem domains include energy, finance, and supply chain, for example).
For claim 26, the specific limitations that recite an abstract idea are:
. . . comparative-analysis operations . . . to compare metadata, learned features, contextual information associated with a service request, and learnings . . ., and identifying relationships, commonalities, and differences among such learned features and metadata to contribute to generating an inference corresponding to a protocol specification, and receiving learned representations . . . to support the comparative-analysis operations;
wherein the protocol specification defines a dialogue-based bilateral interaction protocol comprising steps, conditions, and sequencing of message exchanges occurring in turns between . . . agents;
generating . . . an invocation . . . for the protocol specification in response to a service request received from a client . . . processing the protocol specification, and transmitting the protocol specification . . .;
receiving . . . the invocation and the protocol specification, computing an intermediate model output representing an insight . . ., and transmitting the intermediate model output representing the insight . . .;
receiving . . . the intermediate model output representing the insight and transmitting metadata corresponding to the protocol specification and the intermediate model output representing the insight and contextual information associated with the service request . . .;
generating a computed model output representing an inference . . . by applying the intermediate model output representing the insight and the metadata . . .;
analyzing the metadata and the learnings . . . by comparing learned patterns and features . . . and identifying commonalities and differences among the learned patterns and features, generating the computed model output representing the inference based on the analysis, and transmitting the computed model output representing the inference . . .;
generating an executable protocol implementation using the computed model output representing the inference and the domain-independent protocol specification language; and
executing the generated protocol implementation . . . such that the action associated with the service request is performed.
Claims 26–28, therefore, recite determining protocols for executing a service request, which is the abstract idea of certain methods of organizing human activity because they recite a commercial interaction. This is further evidenced by the specification, which indicates that the service request recited in the claims relates to economic transactions and other interactions in various problem domains, including finance (U.S. Patent App. Pub. No. 2023/0297860, ¶ 110: AEAs transact with each another for wide range of economic transactions; ¶ 62: problem domains include energy, finance, and supply chain, for example).
The judicial exception recited above is not integrated into a practical application. The additional elements of the claims are various generic technologies and computer components to implement this abstract idea (“autonomous economic agents (AEAs)”, “decentralized computing network”, “computing devices”, “processor”, “memory device”, “communication interface”, “software framework”, “protocol generator”, “software modules”, “micro-agents (micro-AEAs)”, “computing arrangement”, “distributed ledger arrangement”, “co-learning software module”, “machine learning (ML) models”, and “software algorithms”). These additional elements are not integrated into a practical application because the invention merely applies the abstract idea to generic computer technology, using the computer to determine and implement a protocol for a service request. Claim 1 does introduce more specific technology—machine learning (ML) models—but again, these are merely being used as generic tools to implement the abstract idea above. The machine learning only provides an alternative means for determining the protocols, through generic pattern and feature comparisons. The additional elements are therefore still merely applying the abstract idea to this technology, using it as a generic tool, rather than creating any type of improvement to the technology itself. Because the invention is using the computer simply as a tool to perform the abstract idea on, the judicial exception is not integrated into a practical application.
Finally, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as discussed above, the additional elements in combination are at a high level of generality such that they amount to no more than mere instructions to apply the abstract idea using generic components. Because merely “applying” the exception using generic computer components cannot provide an inventive concept, the additional elements do not recite significantly more than the judicial exception. Thus, claims 21 and 26 are not patent eligible.
Dependent claims 22–25, 27, and 28 have been given the full two part analysis, analyzing the additional limitations both individually and in combination. The dependent claims, when analyzed individually and in combination, are also held to be patent ineligible under 35 U.S.C. 101.
For claims 22, 23, and 27, the additional recited limitations of these claims merely further narrow the abstract idea discussed above. These dependent claims only narrow the service request recited in claims 1 and 12 by further specifying how the insight and inference are generated—“receiving learnings . . . without sharing metadata”. The limitations of these claims fail to integrate the abstract idea into a practical application because these claims do not introduce additional elements other than the generic components discussed above (“software module”, “machine learning (ML) models”, and “micro-agents (micro-AEAs)”). These claims do introduce more specific technology, machine learning (ML) models, but again, these are merely being used as generic tools to implement the abstract idea above. The chips only provide an alternative means for activating the financial instruments, rather than creating any type of improvement to the technology itself. Claim 1 does introduce more specific technology—machine learning (ML) models—but again, these are merely being used as generic tools to implement the abstract idea above. The machine learning only provides an alternative means for determining the protocols, rather than creating any type of improvement to the technology itself. These dependent claims, therefore, also amount to merely using a computer, in its ordinary capacity, as a tool to perform the abstract idea. Finally, the additional recited limitations of these dependent claims fail to establish that the claims provide an inventive concept because claims that merely use a computer, in its ordinary capacity, as a tool to perform the abstract idea cannot provide an inventive concept.
For claims 24 and 28, the additional recited limitations of these claims merely further narrow the abstract idea discussed above. These dependent claims only narrow the service request recited in claims 1 and 12 by further specifying metadata—“ a technological setup”, “one or more protocols”, “one or more skills”, “one or more connections”, and “the service request”. The limitations of these claims fail to integrate the abstract idea into a practical application because these claims do not introduce additional elements other than the generic components discussed above (“micro-agents (micro-AEAs)”). These dependent claims, therefore, also amount to merely using a computer, in its ordinary capacity, as a tool to perform the abstract idea. Finally, the additional recited limitations of these dependent claims fail to establish that the claims provide an inventive concept because claims that merely use a computer, in its ordinary capacity, as a tool to perform the abstract idea cannot provide an inventive concept.
For claim 25, the additional recited limitations of this claim merely further narrows the abstract idea discussed above. This dependent claim only narrows the service request recited in claim 1 by further specifying the technological setup—“programming language”, “operating system”, “library”, “computational resources”, and “platform”. The limitations of this claim fail to integrate the abstract idea into a practical application because this claim does not introduce additional elements other than the generic components discussed above (“micro-agents (micro-AEAs)”). This dependent claim, therefore, also amounts to merely using a computer, in its ordinary capacity, as a tool to perform the abstract idea. Finally, the additional recited limitations of this dependent claim fails to establish that the claim provides an inventive concept because claims that merely use a computer, in its ordinary capacity, as a tool to perform the abstract idea cannot provide an inventive concept.
Response to Arguments
Claim Rejections Under 35 U.S.C. § 101
Applicant’s arguments filed on December 10, 2025 have been fully considered but they are not persuasive.
First, Applicant argues that the claims recite identifying relationships, commonalities, and differences between learned features and metadata, which is not an abstraction, but is instead a processor-executed process tied to the claimed system architecture. Applicant further explains that the sequence of claimed outputs, computations, and transformations are neither generic or abstract, and are instead directed to a concrete computing environment to construct protocols. Applicant therefore argues that the claims improve computer functioning by enabling cross-model learning and dynamic protocol construction. These improvements identified by Applicant, however, merely specify the determinations made for generating the protocols and implementing the service request. The claims are therefore merely improving the abstract idea by specifying the determinations made, rather than reciting any improvement to the technology itself. The claims are then merely using the technology as a generic tools to make these determinations and implement the results. Thus, claims 21–28 do not include additional elements sufficient to integrate the claims into a practical application.
Next, Applicant argues that the claims recite significantly more than any alleged abstract idea because the claimed features are not well-understood, routine, and conventional. Applicant explains that the standard for showing that the claims are not well-understood, routine, or conventional has not been satisfied by Examiner in the rejection under 35 U.S.C. 101. See Changes in Examination Procedure Pertaining to Subject Matter Eligibility, Recent Subject Matter Eligibility Decision, USPTO Memo (April 19, 2018) (“Berkheimer Memo”). Although Applicant is correct about the requirements under the Berkheimer Memo, these standards are only required when establishing that an additional element is well-understood, routine, or conventional in the Step 2B analysis under the current guidelines. See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 56 n. 36 (Jan. 7, 2019) (“2019 PEG”). The analysis under previous Step 2A Prong Two, however, does not evaluate whether additional elements are well-understood, routine, or conventional, so the Berkheimer Memo requirements need not be considered for this step. See 2019 PEG, 84 Fed. Reg. 50, 55. Furthermore, the Step 2A Prong Two considerations need not be reevaluated under Step 2B, unless the additional elements are concluded to be directed to insignificant extra-solution activity. See 2019 PEG, 84 Fed. Reg. 50, 56. Thus, it is not even necessary to consider whether the additional elements are well-understood, routine, or conventional because merely applying an abstract idea to a computer, as established in Step 2A Prong Two, cannot provide an inventive concept, as required under Step 2B. See MPEP 2106.05(f). For the reasons discussed above, the claims are therefore merely applying the abstract idea to the generic technologies recited, and therefore cannot provide an inventive concept. Thus, claims 21–28 do not include additional elements sufficient to recite significantly more than the judicial exception.
Prior Art Not Relied Upon
The prior art made of record and not relied upon is considered pertinent to Applicant’s disclosure. The following references are pertinent for disclosing various features relevant to the invention, but not all the features or combination of features of the invention, for at least the following reasons:
De Kadt et al., U.S. Patent No. 10,951,540, discloses task parameters for executing tasks.
Jhoney et al., U.S. Patent No. 7,676,539, discloses a distributed environment with service providing agents.
Chessell et al., U.S. Patent App. No. 2018/0285979, discloses storing service history information on a blockchain .
High et al., U.S. Patent App. No. 2018/0349879, discloses a distributed blockchain system for executing contracts.
Conclusion
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/DIVESH PATEL/Examiner, Art Unit 3696