DETAILED ACTION
1. The present application, filed on or after March 13, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
2.. An Amendment was filed May 12, 2026 (hereinafter “Amendment”) and has been entered into the record and fully considered. The Amendment was filed in response to a Non-Final Rejection dated March 5, 2026.
Despite the Amendment to the Claims and Applicant’s remarks, the Rejections under §101 and §103 as set forth in the Non-Final Rejection are hereby maintained. However, the Rejections to the Claims under §103 are on NEW GROUNDS necessitated by the Amendment.
An explanation of the maintained Rejections and a response to Applicant’s arguments are set forth below. Please see the “Conclusion” section of this Action below for important information regarding responding to this Action.
NOTE: interviews are welcome at any stage of prosecution. Please use the AIR form, the link for which can be found at the end of this action, to schedule the interview.
Status of the Claims:
Claims 1 - 20 are pending in this Application.
Independent Claims 1, 9, and 16 were amended in substantially identical fashion.
None of the dependent Claims were amended.
Therefore, the following explanation of the maintained rejections with regard to Claim 1 is considered explanatory of the Rejection as a whole.
With regard to the Amendment:
Claim 1 was amended as follows:
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Summary of the Amendment and Broadest Reasonable Interpretation:
Claim terminology is to be given its plain and ordinary meaning to a person of ordinary skill in the art, consistent with the specification. This is true, unless the terms are given a special meaning. See MPEP §2111.01
Here, no special meaning is detected. As noted in the Amendment, the
changes to Claim 1 relate generally to:
The symbolic rules are defined as logical conditions
Incorporating “symbolic” rules into the nodes of the model
The strength of the node/connection is affected by a determination as to whether the logical condition imposed by the rule is met or not
The requiring step has been modified to be a transmitting step
These terms appear – subject to further consideration – to be defined in the specification based on their plain and ordinary meaning. However, it is noted that Applicant’s comments emphasize that a “neuro-symbolic” model is not tantamount to a regular neural network. Without admitting the veracity of this assertion, the prosecution will continue on that basis.
However, with respect to the limitation relating to the “strength of a relationship,” it would appear clear to a person of ordinary skill in the art that this language refers to the “weight” or “bias” applied to the node(s) and edges of the network, since those concepts also modify the strength of a relationship or correlation between one node and another node. That is, it would be well understood by a person of ordinary skill in the art that in neural networks weights and/or biases are the primary parameter that determines the strength of a relationship between one node and another. Each connection from one node to another has an associated weight, which scales the input signal from the source node before it is passed to the target node.
See para. 0056
With regard to §101:
Respectfully, while the Office recognizes the good faith attempt to render the Claims eligible, the amendments to still lack the specificity required to incorporate a practical application into the abstract idea recited in the claims. Thus, the Claims remain directed to an abstract idea.
With regard to Claim 1, the concepts surrounding encoding a node with an algorithm in which the calculation is given a weighting factor is a high level, conceptual idea. These concepts are well known and generic, as noted above. The specific weights and weighting algorithms are not recited in the Claim. The Claim does not recite what the symbolic rules are nor what the logical conditions are. There is no specificity around what transaction parameters are important to detecting or predicting disputes nor how the rules are conditional nor how they relate to predicting potential disputes.
The Claim provides no specificity in terms of the symbolic rules nor how they are applied or integrated into the model. Only the mere outcome or result of transmitting a requirement for additional authentication is recited. No special functionality is recited. No new computerized components are recited. These limitations recite results or “outcome” of computer processing without specifying “how” a technical problem is solved. That is, the solution of a technical problem is not reflected in the Claim.
Taking the claim elements separately, the function performed by the computer elements at each step of the process is purely typical of integrating logical or symbolic rules into a neural network. There are many scholarly articles on the various approaches for architecture for neuro-symbolic models. Without greater specificity as to “how” certain functions solve a technical problem, the currently recited limitations can be achieved by any general purpose computer without special programming. In short, each step does no more than require a generic computer to perform generic computer functions. Considered as an ordered combination, the computer components of the Claim add nothing that is not already present when the steps are considered separately.
The Claims do not, for example, purport to improve the functioning of the computer elements nor do the claims reflect how an improvement in any other technology or technical field is achieved. Thus, the Claims amount to nothing significantly more than instructions to “apply” the abstract idea of predicting transaction disputes using one well-known ML technique. Such is not sufficient to integrate a practical application in the abstract idea.
That said, the Examiner stands ready to assist the Applicant in revising the Claims to possibly recite eligible subject matter. If desired, please schedule an interview as mentioned above, the AIR form being found in the Conclusion section of this Action.
Accordingly, the Rejection is maintained.
With regard to §103:
Applicant’s amendments and arguments necessitated a new grounds of Rejection:
Claim Rejections - 35 USC § 103
4. 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 of this title, 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.
Claims 1 - 20 are rejected under 35 U.S.C. §103 as being unpatentable over U.S. Patent Publication No. 2021/0374764 to Kramme et al. (hereinafter “Kramme”) in view of U.S. Patent Publication No. 2024/0232900 to Maniulet et al., “ (hereinafter “Maniulet”) and further in view of U.S. Patent Publication No. 2025/0259082 to Crabtree et al. (hereinafter “Crabtree”).
Crabtree is in the same field of endeavor as the claimed invention: the use of a neuro-symbolic model. The Title reads as follows:
“Ai agent decision platform with deontic reasoning and quantum-inspired token management
The Abstract reads:
“A system and method for extending AI-enhanced decision platforms with deontic and normative reasoning capabilities that enhance adjustably autonomous decision-making through a novel integration of symbolic and neural approaches alongside quantum-inspired token management. The invention uses hierarchical and fuzzy deontic logic implementations and quantum-inspired state representations that combine complex amplitudes and phase information to manage obligations, permissions, and prohibitions while maintaining observer awareness to achieve complex goals while incorporating knowledge across multiple expert domains. The system employs dynamic event and spatio-temporal knowledge graphs along with debate mechanisms, enabling high-assurance automated reasoning while preserving explainability through neuro-symbolic integration and information-theoretic metrics. The platform is capable of operating through a federated distributed computational graph architecture that allows for arbitrary scaling while maintaining system coherence and logical consistency using quantum-inspired token operations and phase alignment transformations for optimizing information transfer between states.
Thus, Crabtree is directly on point with the limitations added in the Amendment. One of the use cases for the system of Crabtree is the detection of fraud or related “legal disputes.” (See at least 0133, 0322, and 0470.
This reference teaches that the rules comprise logical conditions:
“[0069] The system further incorporates a set of hierarchical dyadic or fuzzy logic rules that delineate how ephemeral expansions must unify. For instance, a rule might declare “HPC expansions older than threshold T must be ignored” or “Illusions synergy sub-model expansions cannot unify unless validated by a parent domain model.” These constraints ensure the vantage remains consistent with domain policies (e.g., compliance or operational restrictions) and directly encode the “observational approach” the vantage takes in merging expansions.” (Emphasis Added)
Moreover, these rules are integrated or “incorporated” into the nodes and edges of the models. Thus, the weights given to these parameters are adjusted by the encoding of the rules and the strength of these relationships are adjusted according to whether the condition of the rule is met. This is taught throughout Crabtree, but the following is merely one example of such teaching:
“[0175] Quantum knowledge graph network 2810 implements a knowledge representation system through multiple specialized subsystems. An enhanced graph operator 3210 manages the structure and operations of the quantum-inspired knowledge graph through two key components. A quantum embedder 3211 implements a complex embedding pipeline that converts classical knowledge into quantum-inspired representations while preserving essential relationships. When processing a new compliance rule, it first analyzes the rule's content and context to identify key features and relationships. These are then encoded into a quantum state that captures both explicit content through amplitudes and implicit relationships through phase angles. A geometric graph updater 3211 maintains the spatial and relational structure of the graph through sophisticated update mechanisms. It implements graph modification operations that preserve quantum coherence while updating node and edge properties. For example, when adding a new compliance rule, the updater computes optimal edge weights and phase relationships to properly integrate the rule into the existing knowledge structure. The updater also implements topology preservation algorithms that maintain important graph properties during modifications, ensuring that the quantum-inspired representation remains consistent and meaningful.” (Emphasis Added)
See also 0171, 0110, 0118, and 0163.
It should also be noted that deontic reasoning is a branch of logic that deals with normative concepts such as obligation, permission, and prohibition, providing a formal framework for understanding ethical and legal reasoning. Thus, these teachings of Crabtree are directly on point with the logical rules of the claimed invention which are directed to parameters of a transaction that may lead to a dispute.
Therefore, it would have been obvious to one of ordinary skill in the relevant art at the time of filing the claimed invention to have modified the combined ML model of Kramme in view of Maniulet, in which model predicts fraud which of necessity would lead to disputes regarding financial transactions, to add the neuro-symbolic teachings of Crabtree. The motivation to do so comes from Kramme. It teaches the use of neural networks for fraud prediction. It would greatly enhance the efficiency and accuracy of the system of Kramme in view of Maniulet to add the neuro-symbolic model teachings of Crabtree..
Therefore, the Rejection of these Claims under §103 is also maintained.
Response to Arguments
3. Applicant's arguments set forth in the Remarks section of the Amendment have been fully considered but they are not persuasive.
With regard to section 101 rejection, Applicant argues as follows:
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Thus, it appears that Applicant is under the misunderstanding that the recited Abstract Idea is a mental process. Such is not the case. As explained in detail in the Non-Final Rejection, the recited abstract idea is a common method of organizing human behavior, namely, the fundamental economic practice of using a ML model to detect fraud and predict disputes. See Non-Final Rejection, p. 3 – 4.
Therefore, these arguments are not persuasive.
With regard to §103:
Applicant’s arguments with respect to the Rejections under §103 are moot in view of the new grounds of Rejection.
A follow up interview is encouraged to discuss the merits of this Application.
Conclusion
5. Applicant should carefully consider the following in connection with this Office Action:
A. Finality
THIS ACTION IS MADE FINAL. Applicant’s amendments to the Claims necessitated the new grounds of Rejection. See MPEP § 706.07. 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 extension fee 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 date of this final action.
B. Search and Prior Art
The search conducted in connection with this Office Action, as well as any previous Actions, encompassed the inventive concepts as defined in the Applicant’s specification. That is, the search(es) included concepts and features which are defined by the pending claims but also pertinent to significant although unclaimed subject matter. Accordingly, such search(es) were directed to the defined invention as well as the general state of the art, including references which are in the same field of endeavor as the present application as well as related fields (e.g. the use of large language models (LLM’s) and other transformers for predicting the likelihood of a dispute). Indeed, there is a plethora of prior art in these fields.
Therefore, in addition to prior art references cited and applied in connection with this and any previous Office Actions, the following prior art is also made of record but not relied upon in the current rejection:
U.S. Patent Publication No. 2025/0259075 to Crabtree et al. This reference relates to the concept of the use of neuro-symbolic principles in connection with large language models.
U.S. Patent No. 12,561,720 to Hassen. This reference relates to the concept of the use of a neuro-symbolic graph model.
C. Responding to this Office Action
In view of the foregoing explanation of the scope of searches conducted in connection with the examination of this application, in preparing any response to this Action, Applicant is encouraged to carefully review the entire disclosures of the above-cited, unapplied references, as well as any previously cited references. It is likely that one or more such references disclose or suggest features which Applicant may seek to claim. Moreover, for the same reasons, Applicant is encouraged to review the entire disclosures of the references applied in the foregoing rejections and not just the sections mentioned.
D. Interviews and Compact Prosecution
The Office strongly encourages interviews as an important aspect of compact prosecution. Statistics and studies have shown that prosecution can be greatly advanced by way of interviews. Indeed, in many instances, during the course of one or more interviews, the Examiner and Applicant may reach an agreement on eligible and allowable subject matter that is supported by the specification.
Interviews are especially welcomed by this examiner at any stage of the prosecution process. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool (e.g. TEAMS).
To facilitate the scheduling of an interview, the Examiner requests the use of the AIR form as follows:
USPTO Automated Interview Request http://www.uspto.gov/interviewpractice.
Other forms of interview requests filed in this application may result in a delay in scheduling the interview because of the time required to appear on the Examiner's docket. Thus, the use of the AIR form is strongly encouraged.
E. Communicating with the Office
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILLIAM BUNKER whose telephone number is (571)272-0017. The examiner can normally be reached on M - F 8:30AM - 5:30PM, Pacific.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Abhishek Vyas, can be reached at 571-270-1836. Information regarding the status of an application, whether published or unpublished, may be obtained from the “Patent Center” system. For more information about the Patent Center system, https://patentcenter.uspto.gov/
/William (Bill) Bunker/
U.S. Patent Examiner
AU 3691
william.bunker@uspto.gov
(571) 272-0017
June 1, 2026
/ABHISHEK VYAS/Supervisory Patent Examiner, Art Unit 3691
Prosecution Insights