DETAILED ACTION
This action is responsive to the pending claims, 1-20, received 20 March 2026. Accordingly, the detailed action of claims 1-20 is as follows:
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 21 July 2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Terminal Disclaimer
The terminal disclaimer filed on 21 July 2026 disclaiming the terminal portion of any patent granted on this application has been reviewed and is accepted. The terminal disclaimer has been recorded.
Specification
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim 1-3, 5-6, 7, 14, 17-19 rejected under 35 U.S.C. 103 as being unpatentable over Meirosu et al (US 20240291664 A1, hereafter referred to as Meirosu) in view of Chen (US 12418417 B1, hereafter referred to as Chen).
Regarding claim 1, Meirosu teaches a system comprising: at least one hardware processor (Meirosu [0122-0123, 0132-0133]); and
at least one non-transitory memory storing instructions (Meirosu [0134, 0122]), which, when executed by the at least one hardware processor, cause the system to:
obtain a request to store an operational context (Meirosu [Fig 2-3, 0065] teaches a device instructing a blockchain client comprised in the device to perform storing of first data in a blockchain ledger running on a separate blockchain network, wherein the data is linked to a charging data record);
maintain, on a distributed network, one or more data structures that each includes a respective cryptographic identifier for the at least one AI-based agent (Meirosu [0060-0061] teaches maintaining a distributed ledger comprising an extendable list of blocks linked using cryptographic techniques wherein the data in the blocks comprises one or more CDR identifiers and one or more hash values of a CDR);
obtain, from a computing device, an input (Meirosu [0085] teaches a device obtains, via sending a request using the index, hash value of the CDR and the CDR identifier);
determine, using the distributed network, at least one data structure based on a particular cryptographic identifier (Meirosu [0086] teaches using the index to find where in the blockchain ledger the block containing the hash value associated to a CDR entry is stored), wherein the one or more data structures are linked to respective operational context which corresponds to least a portion of the operational context (Meirosu [0068] teaches the hash value of the CDR and the CDR identifier are stored in the same transaction or block of the blockchain); and
cause transmission of a representation of a respective AI-based agent associated with the at least one data structure to the computing device (Meirosu [0085] teaches providing the first hash value of the CDR and the CDR identifier from the blockchain to the blockchain client running on the device, wherein the blockchain ledger is running on a separate blockchain network).
However, Meirosu does not explicitly teach obtain a request to store an operational context linked to one or more respective AI-based agents that are each a software entity configured to semi-autonomously or autonomously execute one or more tasks based on a respective objective function, wherein the operational context includes one or more of: an agent identifier, a domain indicator, a data access permission, workflow contribution data, or a cryptographic credential; cause generation of, for at least one AI-based agent of the one or more respective AI-based agents, a cryptographic identifier by applying one or more functions to a representation of at least a portion of a corresponding operational context; obtain, from a computing device, an input to identify a particular AI-based agent of the one or more respective AI-based agents based on a particular operational context.
Chen, in an analogous art, teaches obtain a request to store an operational context linked to one or more respective AI-based agents (Chen [Abstract, fig 7-705 and 18:6-18] teaches receiving a registration request from an AI agent) that are each a software entity configured to semi-autonomously or autonomously execute one or more tasks based on a respective objective function (Chen [1:15-60] teaches AI agents performing tasks autonomously for a particular industry or domain), wherein the operational context includes one or more of:
an agent identifier, a domain indicator (Chen [13:10-16] teaches roles and permissions assigned to the AI agent), a data access permission (Chen [12:53-56] teaches the identity token controls access based on assigned roles), workflow contribution data (Chen [12:16-34]) teaches roles determine an AI agents functions and actions and expected workflows, or a cryptographic credential (Chen [5:4-16] teaches the hash value is generated based on training dataset signatures and public key signatures stored in the blockchain);
cause generation of, for at least one AI-based agent of the one or more respective AI-based agents, a cryptographic identifier by applying one or more functions to a representation of at least a portion of a corresponding operational context (Chen [11:15-24 and 5:4-16] teaches a hash value generated over a an AI agent’s binary and model parameters);
obtain, from a computing device, an input to identify a particular AI-based agent of the one or more respective AI-based agents based on a particular operational context (Chen [19:6-30] teaches receiving a request to authenticate a particular AI agent based on a token associated with a specific operational context wherein the blockchain is traversed to retrieve one or more records associated with the AI agent based on the identity token).
It would have been obvious for a person having ordinary skill in the art, before the effective filing date of the claimed invention, to modify Meirosu in view of Chen in order to configure the system, as taught by Meirosu to obtain a request to store an operational context linked to one or more respective AI-based agents that are each a software entity configured to semi-autonomously or autonomously execute one or more tasks based on a respective objective function, wherein the operational context includes one or more of: an agent identifier, a domain indicator, a data access permission, workflow contribution data, or a cryptographic credential; cause generation of, for at least one AI-based agent of the one or more respective AI-based agents, a cryptographic identifier by applying one or more functions to a representation of at least a portion of a corresponding operational context, as taught by Chen.
One of ordinary skill in the art would have been motivated in order to permit any action performed by or to and AI agent to be recorded in a blockchain which substantially enhances the computer network security where the AI agents are deployed due to immutability of blockchains (Chen [3:15-25]).
Regarding claim 2, Meirosu-Chen teaches the limitations of claim 1, as rejected above.
Additionally, Meirosu-Chen teaches the system wherein the system is further caused to:
detect one or more of a transaction or data access of a dataset associated with a particular AI-based agent (Chen [5:18-28] teaches attributes of an AI agent changing including re-training, according to training data used to train the AI model [5:8-10], requires the AI agent to re-register, recompute its model hash for storage on the blockchain [11:48-54]); and record, on the distributed network, an event record that includes one or more of a timestamp or an identifier of the dataset (Chen [11:48-54] teaches the AI model, training data fingerprints and hyperparameters are stored on the blockchain including re-trained models).
Regarding claim 3, Meirosu-Chen teaches the limitations of claim 1, as rejected above.
Additionally, Meirosu-Chen teaches the system wherein the distributed network is a ledger network (Meirosu [0062] teaches a blockchain for use as a distributed ledger managed by the peers of a blockchain network).
Regarding claim 5, Meirosu-Chen teaches the limitations of claim 1, as rejected above.
Additionally, Meirosu-Chen teaches the system wherein the distributed network comprises a plurality of nodes that maintain synchronized copies of the one or more data structures (Meirosu [0062] teaches a blockchain for use as a distributed ledger managed by a plurality of nodes or peers in a blockchain network).
Regarding claim 6, Meirosu-Chen teaches the limitations of claim 1, as rejected above.
Additionally, Meirosu-Chen teaches the system wherein the input is received from an AI model (Meirosu [0085] teaches the blockchain client obtains, via a request including the first index, the first hash value of the CDR and the CDR identifier).
Regarding claim 7, it does not teach or further limit over the limitations presented above with respect to claim 1.
Therefore, claim 7 is rejected for the same reasons set forth above regarding claim 1.
Regarding claim 14, it does not teach or further limit over the limitations presented above with respect to claim 1.
Therefore, claim 14 is rejected for the same reasons set forth above regarding claim 1.
Regarding claim 17, Meirosu-Chen teaches the limitations of claim 14, as rejected above.
Additionally, Meirosu-Chen teaches the computer implemented method further comprising: determining a score for each AI-based agent based on one or more performance metrics associated with the AI-based agent (Chen [9:3-24; 10:43-56]).
Regarding claim 18, Meirosu-Chen teaches the limitations of claim 14, as rejected above.
Additionally, Meirosu-Chen teaches the computer implemented method wherein the at least one data structure is a blockchain-based data structure (Meirosu [0062] teaches a blockchain for use as a distributed ledger managed by a plurality of nodes or peers in a blockchain network).
Regarding claim 19, Meirosu-Chen teaches the limitations of claim 14, as rejected above.
Additionally, Meirosu-Chen teaches the computer implemented method further comprising: obtaining an updated operational context of a particular AI-based agent (Chen [5:18-28] teaches attributes of the AI agent changing); and generating a new secure identifier different from the particular secure identifier by applying the one or more functions to a representation of the updated operational context (Chen [5:18-28] teaches an agent re-registering such that a new identity token and linked information is stored on the blockchain [18:19-40]).
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Allowable Subject Matter
Claim 4, 8-13, 15-16, 20 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Double Patenting
The nonstatutory double patenting rejection presented in the previous office action has been withdrawn in view of the applicant’s terminal disclaimer filed 21 July 2026.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHEAN TOKUTA whose telephone number is (571)272-5145. The examiner can normally be reached M-TH 630-430.
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SHEAN TOKUTA
Primary Examiner
Art Unit 2446
/SHEAN TOKUTA/Primary Examiner, Art Unit 2419
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