DETAILED ACTION
This action is responsive to amendment filed on February 23rd, 2026.
Claims 1~20 are examined.
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 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.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1~20 are rejected under 35 U.S.C. 103 as being unpatentable over Smith et al. hereinafter Smith (U.S 2020/0396137), Beard et al. hereinafter Beard (U.S 2024/0073241), and Smith et al. hereinafter Smith (U.S 2016/0204934) in view of Binyamini et al. hereinafter Binyamini (U.S 2023/0412635).
Regarding Claim 1,
Smith taught a method for controlling operations of an electronic device, comprising:
receiving, by a processor, first information associated with a first iteration of artificial intelligence operations performed by an ontogenesis engine [¶147, capture and storage of knowledge (e.g., new and existing data objects); ¶146];
generating, by the processor, a behavior data object using the first information [¶147, capture and storage of knowledge (e.g., new and existing data objects); ¶146];
building, by the processor, a DNA AI intelligence structure, wherein the DNA AI intelligence structure comprises the behavior data object linked to a root data object [¶149, information identifying the behavior of the people or data objects associated with the situation, the computing device(s) associated with the situation, the purpose of the computing device operations/behaviors, the network nodes associated with the situation, the purpose of network node operations/behaviors],
wherein the root data object comprises information concerning the electronic device [¶191, ontogenesis memory object comprises…related information about a concrete physical individual, vehicle, network node, or item];
receiving, by a processor, second information associated with a second iteration of artificial intelligence operations performed by the ontogenesis engine [¶165, a new information object and information specifying the new information object's relationship with the another data object are stored in the knowledge data store];
generating, by the processor, a next behavior data object using the second information [¶166, the sets of parameters, factors and/or coefficients used in previous simulations are used to generate new sets of parameters, factors and/or coefficients];
adding, by the processor, the next behavior data object to the DNA AI intelligence structure so as to be linked directly to the root data object or indirectly to the root data object via the behavior data object [¶165, If so, then a new information object and information specifying the new information object's relationship with the another data object are stored in the knowledge data store, and subsequently used in simulation operations]; and
using knowledge gained from the DNA AI intelligence structure about how artificial intelligence engines arrive at answers with confidence to modify or advance the artificial intelligence operations [¶167, the new sets of parameters, factors and/or coefficients are used by module 2414 to simulate certain behaviors by individual(s), vehicle(s) and/or network nodes in the context of the situation; ¶187, analyzing the system action(s) to determine a confidence level that a given result will occur in view of the set of tolerances determined 2416 (see ¶173) and a probability of success].
performing, by the ontogenesis engine, the modified or advanced artificial intelligence operations to facilitate simulation of one or more sets of actions that could occur in a context of a given situation, wherein the simulation generates predicted consequences resulting from a performance of behaviors by electronic device [¶170, after the simulations are performed, the predicted consequences are then evaluated to determine their relative values based on certain criteria. In some scenarios, the relative values are determined based on whether or not certain actions, conditions or results are reflected by the predicted consequences]; and
controlling operations of the electronic device using parameters of the predicted consequences [¶175, determining which system actions from a set of allowable actions should be performed in view of the selected predicted consequence];
wherein the DNA Al intelligence structure comprises branches of behavior data objects defining the reasoning of the ontogenesis engine with growth demarcations, the growth demarcations marking specific points of growth within the DNA Al intelligence structure [¶184, given a particular growth of CMC, the EmergS0 will grow over time in accordance with the following mathematical equation; ¶186, where CMC represents a mathematical time growth value (number) determined from historical data or ontogenic insight, or algorithms within a range of {0⇄x}, where higher values represent a more mature or capable actor (of actions/behaviors against the system). Lower values are derived from historical data where an action (behavior) was successful against an opposing action (behavior from an actor). In the cyber maneuver applications, the system actions can include the modification of one or more behavior models, CBMs and/or mission plans].
Smith did not specifically teach a DNA Al intelligence structure defining reasoning of the ontogenesis engine for determining one or more actions to be taken by the electronic device in view of a stimuli and/or an impingement action.
Beard taught DNA AI intelligence structure defining reasoning of the ontogenesis engine for determining one or more actions to be taken by the electronic device in view of a stimuli and/or an impingement action [¶65, the rules and the behavior of the target computer system (corresponding to an instance of a KB) are processed by a knowledge-driven reasoning component of the knowledge-based IR component 312; see examples of the KB in ¶61~¶64].
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention was made, to combine, Beard’s teaching of limitations with the teachings of Smith, because the combination would improve the robustness of intrusion response determination, reducing the likelihood of responding inappropriately to behavior of the computer system, which can improve the performance of the computer system [Beard: ¶38].
The combination of Smith and Beard did not specifically teach wherein the DNA Al intelligence structure comprises branches of behavior data objects defining the reasoning of the ontogenesis engine with embedded security, the embedded security comprising at least unique code identifiers added to links linking the behavior data objects.
Smith taught wherein the DNA Al intelligence structure comprises branches of behavior data objects defining the reasoning of the ontogenesis engine with embedded security, the embedded security comprising at least unique code identifiers added to links linking the behavior data objects within the hierarchical node-link structure [¶85, mission plan can be stored in the module(s) so as to be associated with at least one identifier for a user of the computer network, at least one identifier for a mission of the enterprise, at least identifier for the mission plan; ¶38, the mission plan can be downloaded to the module in an encrypted or decrypted form. In the encrypted scenarios, a cryptographic key and/or algorithm can be obtained from a remote data store, a local data store; ¶112, based on the results of the simulation, at least one graph is generated which can be subsequently used to identify any conflicts in module behaviors as a result of implementing the mission plans].
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention was made, to combine, Smith’s teaching of limitations with the teachings of Smith and Beard, because the combination would provide a computer network which is dynamically maneuverable to defend against malicious attack [Smith: ¶35].
The combination of Smith, Beard, and Smith did not specifically teach wherein the DNA AI intelligence structure comprises a hierarchical node-link structure.
Binyamini taught the DNA AI intelligence structure comprises a hierarchical node-link structure [¶54, AgiRem service 210 provides a list of efficient and effective remediation recommendations using data from the vulnerability analytics module 236 of the AgiInt service 212. In some examples, the graph explorer 232 analyzes each feature (e.g., nodes, edges between nodes, properties) to identify any condition (e.g., network/system configuration and vulnerabilities) that can lead to cyber impacts; ¶68; ¶69].
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention was made, to combine, Binyamini’s teaching of limitations with the teachings of Smith, Beard, and Smith, because the combination would enrich security findings reports with potential attack scenarios and other exploitation information, and recommend the most effective countermeasures to avoid a detected vulnerability [Binyamini: ¶35].
Regarding Claim 2,
Smith taught wherein a linkage between the behavior data object and the next behavior data object specify a temporal order of at least two behaviors that the electronic device is able to perform [¶143, analyzes temporal and contextual knowledge; ¶144, a behavior model modified or revised over time].
Regarding Claim 3,
Smith taught further comprising: determining if a behavior associated with the next behavior data object is part of a sequence of behaviors; and deciding that the next behavior data object should be indirectly linked to the root data object via the behavior data object when a determination is made that the behavior associated with the next behavior data object is part of the sequence of behaviors ¶191, topics linked to other topics; ¶192, Fig. 25].
Regarding Claim 4,
Smith taught wherein the behavior data object comprises an AI DNA intelligence genealogy layer and an AI behavior genealogy layer, the AI behavior genealogy layer containing the first information received from the ontogenesis engine and the AI DNA intelligence genealogy layer comprising other information that was not received from the ontogenesis engine [¶148; ¶165].
Regarding Claim 5,
Smith taught wherein the first information comprises a security code associated with an individual or object, a birth date of an individual or object, growth aspects of an individual or object, a state of an individual or object, a lifespan of an individual or object, an age of an individual or object, an individual’s or object’s morality, an individual’s or object’s ethics, an individual’s or object’s etiquette, behavior definition(s), an urgency for behavior performance, a behavior importance, behavior priorities, individual’s or object’s boundaries, a mission ontology, a maneuver ontology, and/or a relationship between the individual or object and another individual or object [¶192, Fig. 25].
Regarding Claim 6,
Smith taught wherein the other information comprises a human language for defining the DNA AI intelligence structure and a computer language in which the DNA AI intelligence structure is created [¶81, the use of a common language and models for deriving maneuver scheme definition].
Regarding Claim 7,
Smith taught further comprising: analyzing an outcome from performance of behavior associated with the next behavior data object to determine whether a goal has been met or achieved; and assigning a good behavior marking to the next behavior data object when a determination is made that the goal was met or achieved, or assigning a bad behavior marking to the next behavior data object when a determination is made that the goal was not met or achieved [¶158, correlating behavior goals].
Regarding Claim 8,
Smith taught further comprising: determining whether a task has ever been performed by the electronic device; analyzing the DNA AI intelligence structure to identify one or more data objects that have been assigned a good behavior marking; and communicating a behavior, an analytic setting and a metric setting of the identified one or more data objects to the ontogenesis engine to cause the electronic device to perform the behavior [¶198, greater good functions].
Regarding Claim 9,
Smith taught further comprising analyzing an outcome from the electronic devices performance of the behavior [¶173].
Regarding Claim 10,
Smith taught further comprising selectively growing the DNA AI intelligence structure based on said analyzing [¶184~¶186].
Regarding Claims 11~20, the claims are similar in scope to claim(s) 1~10 and therefore, rejected under the same rationale.
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 HEE SOO KIM whose telephone number is (571)270-3229. The examiner can normally be reached M-F 9AM-5PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Nicholas Taylor can be reached on (571) 272-3889. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HEE SOO KIM/Primary Examiner, Art Unit 2443