Prosecution Insights
Last updated: October 02, 2026
Application No. 18/821,414

SYSTEMS AND METHODS FOR PROVIDING DYNAMIC INTERACTIONS WITH NON-PLAYER CHARACTERS (NPCS) IN VIDEO GAMES

Final Rejection §103
Filed
Aug 30, 2024
Examiner
SITTA, GRANT
Art Unit
2622
Tech Center
2600 — Communications
Assignee
Adeia Technologies Inc.
OA Round
2 (Final)
72%
Grant Probability
Favorable
3-4
OA Rounds
11m
Est. Remaining
86%
With Interview

Examiner Intelligence

Grants 72% — above average
72%
Career Allowance Rate
689 granted / 952 resolved
+10.4% vs TC avg
Moderate +13% lift
Without
With
+13.3%
Interview Lift
resolved cases with interview
Typical timeline
3y 0m
Avg Prosecution
27 currently pending
Career history
992
Total Applications
across all art units

Statute-Specific Performance

§101
2.5%
-37.5% vs TC avg
§103
63.5%
+23.5% vs TC avg
§102
22.1%
-17.9% vs TC avg
§112
6.1%
-33.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 952 resolved cases

Office Action

§103
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 filed 7/15/2026 have been fully considered but they are not persuasive. Applicant contends: PNG media_image1.png 336 660 media_image1.png Greyscale Examiner respectfully disagrees. Perry states: [0015] Various systems, apparatuses, and methods for creating human-like non-player character behavior with reinforcement learning and supervised learning are disclosed herein. In one implementation, an artificial intelligence (AI) engine creates a non-player character (NPC)… [0057] In some implementations a more complex AI engine mastermind is employed. For example, in one implementation, a more complex AI engine controls several simpler AI engines to support the player or compete against the player. In this implementation, a command structure is utilized as well as different levels of AI engine complexity. The different levels of complexity give rise to understanding the different performance characteristics of the different complexities. [0058] In one implementation, a mastermind does not exist at the beginning of the game. Rather, one of the AI engines learns from its own actions and also learns from the experiences of other AI engines to become a more capable AI engine. As the AI engine becomes more capable through reinforcement learning, the AI engine hires other AI engines gradually as the AI engine gets more powerful. Also, in one implementation, one AI engine is programmed to manipulate other AI engines. The other agents are affected in varying degrees based on their individual characteristics. Generally speaking, these implementations use AI agents that think independently and are able to receive orders. Also, in some cases, an AI agent ignores orders from a central controller based on reinforcement learning. Examiner notes it appears each AI engine can be a NPC and the AI engines act to effect other AI engines. Examiner understands a node to be In AI systems, a node is generally a computational unit that: receives input data (raw, processed, or model outputs), applies computation or logic (e.g., model inference, transformation, aggregation), produces output for the next stage or consumer. Examiner understands an edge represents the connection between nodes, defining how data and control flow through the network or graph. As noted above it appears each NPC can be an AI engine, or a node, and affect other AI engines (other NPCs) and the interaction is the edge. Applicant further contends: PNG media_image2.png 272 706 media_image2.png Greyscale The test for obviousness is not whether the features of a secondary reference may be bodily incorporated into the structure of the primary reference; nor is it that the claimed invention must be expressly suggested in any one or all of the references. Rather, the test is what the combined teachings of the references would have suggested to those of ordinary skill in the art. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981). Perry teaches systems, apparatuses, and methods for creating human-like non-player character (NPC) behavior with reinforcement learning (RL) are disclosed. An artificial intelligence (AI) engine creates a NPC that has seamless movement when accompanying a player controlled by a user playing a video game. The AI engine is RL-trained to stay close to the player but not get in the player's way while acting in a human-like manner. Also, the AI engine is RL-trained to evaluate the quality of information that is received over time from other AI engines and then to act on the evaluated information quality. Each AI agent is trained to evaluate the other AI agents and determine whether another AI agent is a friend or a foe. In some cases, groups of AI agents collaborate together to either help or hinder the player. The capabilities of each AI agent are independent from the capabilities of other AI agents. Haung teaches in a method for controlling a non-player character (NPC), each of a plurality of NPCs in an NPC group is controlled through a respective individual control logic of a plurality of individual control logics and a status parameter of the respective NPC. The status parameter corresponding to at least a first NPC in the NPC group is modified, by processing circuitry and through a group control logic, based on a modifying condition between a virtual character and a first NPC in the NPC group. An interaction between the NPC and the virtual character is controlled, through the individual control logic of the NPC, based on the modified status parameter of the NPC. Apparatus and non-transitory computer-readable storage medium counterpart embodiments are also contemplated. Examiner believes it would have been obvious to one of ordinary skill in the art to modify an interaction by a UPC with a first NPC (e.g. fig. 7 different independent personalities) and impacts a second NPC (fig. 3 302-306), or in other words, have groups of individual personalities, in order to determine more complex behavior games [005-0010]. Examiner understands the personal impact graph to be the interaction of NPCs. See Applicant’s specification [0052] In some embodiments, based on the relations formed between the NPCs in the video game environment, the video game system may, by modifying the personality vector of a first NPC, cause a personality vector of a second NPC to be modified. In some implementations, the first NPC is NPC 102, and the second NPC is NPC 114 of FIG. 1A. In some embodiments, the video game system represents the relations between the various NPCs in the video game environment by generating, or otherwise accessing, a personality impact graph (e.g., personality impact graph 108) PNG media_image3.png 816 698 media_image3.png Greyscale If Applicant thinks an interview would help expedite prosecution the Examiner is open to an interview. 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. Claim(s) 1, 4, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Perry et al (2022/0309364) hereinafter, Perry in view of Huang (2026/0007969) hereinafter, Huang. In regards to claim 1, Perry teaches a computer-implemented method, comprising (abstract): identifying a plurality of non-player characters (NPCs) of a video game (fig. 7 NPCs), wherein the plurality of NPCs is associated with a plurality of personality vectors (fig. 7 710-720 personality vectors (fig. 2 and 3 AI)[0018, 0033], respectively, and wherein a respective NPC interacts with a user-playable character (UPC) (fig. 8 (805)) in the video game based at least in part on one or more characteristics represented in the respective personality vector corresponding to the respective NPC [0018, 0029,0062,0071-0074] (fig. 7 (705 and 710-725)); PNG media_image4.png 618 838 media_image4.png Greyscale PNG media_image5.png 660 830 media_image5.png Greyscale accessing a personality impact graph comprising a plurality of nodes and a plurality of edges (fig. 2 and 3 nodes and edges), wherein the plurality of nodes respectively correspond to the plurality of NPCs [0031-0033, 0070-0082] (fig. 4 (420 to 440 to 460)), and wherein at least a portion of the plurality of edges indicate how an interaction by the UPC with a first NPC of the plurality of NPCs impacts a personality vector of a second NPC of the plurality of NPCs [0074]; PNG media_image6.png 812 542 media_image6.png Greyscale PNG media_image7.png 826 716 media_image7.png Greyscale Perry fails to expressly teach detecting the interaction between the UPC and the first NPC; based at least in part on the detected interaction and the personality impact graph, modifying the personality vector of the second NPC; and based on the modified personality vector of the second NPC, dynamically causing the second NPC to interact with the UPC. However, Huang teaches detecting the interaction between the UPC and the first NPC;(fig. 3 (304)) based at least in part on the detected interaction modifying the personality vector of the second NPC; and (fig. 3 (306, fig. 40 402-406, fig. 5 501 and 502)[0051-0057]. [0045] For example, the computer device modifies, by using the group control logic, an initial status parameter corresponding to the at least one NPC in the NPC group in response to the virtual character 10 and the first NPC entering an interaction scene. It would have been obvious to one of ordinary skill in the art to modify the teachings of Perry to further include detecting the interaction between the UPC and the first based at least in part on the detected interaction modifying the personality vector of the second NPC as taught by Huang in order to determine more complex behavior games [005-0010] Therefore, Perry in view of Huang teaches detecting the interaction between the UPC and the first NPC;(fig. 3 (304))Huang based at least in part on the detected interaction (fig. 1 (10 and NPC2)) Huang and the personality impact graph [0031-0033, 0070-0082] (fig. 4 (420 to 440 to 460)) Perry, modifying the personality vector of the second NPC (fig. 11 (1100))Perry; and based at least in part on the modified personality vector of the second NPC, dynamically causing the second NPC to interact with the UPC [0078-0085] Perry. In regards to claim 20, Perry teaches a system comprising: a memory; a control circuitry configured to (abstract): identify a plurality of non-player characters (NPCs) of a video game, (fig. 7 NPCs), wherein the plurality of NPCs is associated with a plurality of personality vectors (fig. 7 710-720 personality vectors (fig. 2 and 3 AI)[0018, 0033], respectively, and wherein a respective NPC interacts with a user-playable character (UPC) in the video game based on one or more characteristics represented in the respective personality vector corresponding to the respective NPC; [0018, 0029,0062,0071-0074] (fig. 7 (705 and 710-725)); access a personality impact graph comprising a plurality of nodes and a plurality of edges, (fig. 2 and 3 nodes and edges), wherein the plurality of nodes respectively correspond to the plurality of NPCs, wherein at least a portion of the plurality of edges indicate how an interaction by the UPC [0031-0033, 0070-0082] (fig. 4 (420 to 440 to 460)), with a first NPC of the plurality of NPCs impacts a personality vector of a second NPC of the plurality of NPCs [0074];, and wherein the personality impact graph is stored in the memory; [0024 and 0027] Perry fails to expressly teach detect the interaction between the UPC and the first NPC; However, Huang teaches detecting the interaction between the UPC and the first NPC;(fig. 3 (304)) based at least in part on the detected interaction modifying the personality vector of the second NPC; and (fig. 3 (306, fig. 40 402-406, fig. 5 501 and 502)[0051-0057]. [0045] For example, the computer device modifies, by using the group control logic, an initial status parameter corresponding to the at least one NPC in the NPC group in response to the virtual character 10 and the first NPC entering an interaction scene. It would have been obvious to one of ordinary skill in the art to modify the teachings of Perry to further include detecting the interaction between the UPC and the first based at least in part on the detected interaction modifying the personality vector of the second NPC as taught by Huang in order to determine more complex behavior games [005-0010] Therefore, Perry in view of Huang teaches detect the interaction between the UPC and the first NPC; ;(fig. 3 (304))Huang based at least in part on the detected interaction and the personality impact graph, modify the personality vector of the second NPC (fig. 1 (10 and NPC2)) Huang; and[0031-0033, 0070-0082] (fig. 4 (420 to 440 to 460)) (fig. 11 (1100))Perry; , based on the modified personality vector of the second NPC, dynamically cause the second NPC to interact with the UPC. [0078-0085] Perry. In regards to claim 4, Perry in view of Haung teaches the method of claim 1, wherein the plurality of edges of the personality impact graph is based at least in part on respective locations of the plurality of NPCs in the video game.[0097] the distance between NPC and virtual character modifies the status parameter. Huang. Claim(s) 12-13, 16 and 30 is/are rejected under 35 U.S.C. 103 as being unpatentable over Perry et al (2022/0309364) hereinafter, Perry and Huang in view of Keller (2024/0066401) hereinafter, Keller. In regards to claim 12, Perry and Huang fail to teach the method of claim 1, further comprising: identifying a first UPC of a plurality of UPCs and at least one second UPC of the plurality of UPCs, wherein the first UPC is the UPC; determining a base personality vector and a plurality of personalized personality vectors of the first NPC, wherein a first personalized personality vector of the plurality of personalized personality vectors influences interactions between the first NPC and the first UPC, and wherein a second personalized personality vector of the plurality of personalized personality vectors influences interactions between the first NPC and the second UPC; based at least in part on the detected interaction between the first UPC and the first NPC: modifying the first personalized personality vector; and generating a first resulting personality vector of the first NPC based on the base personality vector of the first NPC and the modified first personalized personality vector, wherein the first resulting personality vector of the first NPC influences subsequent interactions between the first NPC and the first UPC. However, Keller teaches further comprising: identifying a first UPC of a plurality of UPCs and at least one second UPC of the plurality of UPCs (fig. 7 user A and user B), wherein the first UPC is the UPC (fig. 4 (401)); determining a base personality vector and a plurality of personalized personality vectors of the first NPC [0067], wherein a first personalized personality vector of the plurality of personalized personality vectors influences interactions between the first NPC and the first UPC (fig. 4 (401-403)), and wherein a second personalized personality vector of the plurality of personalized personality vectors influences interactions between the first NPC and the second UPC (fig. 4 (404) [0067-0074]; based at least in part on the detected interaction between the first UPC and the first NPC[0074-0080]: modifying the first personalized personality vector; and generating a first resulting personality vector of the first NPC based on the base personality vector of the first NPC and the modified first personalized personality vector, wherein the first resulting personality vector of the first NPC influences subsequent interactions between the first NPC and the first UPC (fig. 4 (401-407)). It would have been obvious to one of ordinary skill in the art to modify the teachings of Perry and Haung to further include identifying a first UPC of a plurality of UPCs and at least one second UPC of the plurality of UPCs, wherein the first UPC is the UPC; determining a base personality vector and a plurality of personalized personality vectors of the first NPC, wherein a first personalized personality vector of the plurality of personalized personality vectors influences interactions between the first NPC and the first UPC, and wherein a second personalized personality vector of the plurality of personalized personality vectors influences interactions between the first NPC and the second UPC; based at least in part on the detected interaction between the first UPC and the first NPC: modifying the first personalized personality vector; and generating a first resulting personality vector of the first NPC based on the base personality vector of the first NPC and the modified first personalized personality vector, wherein the first resulting personality vector of the first NPC influences subsequent interactions between the first NPC and the first UPC as taught by Kerry in order better provide truly interactive stories [003-006] In regards to claim 13, Perry in view of Huang and Keller teaches the method of claim 12, further comprising: detecting an interaction between the second UPC and the first NPC; and based at least in part on the second interaction: modifying the second personalized personality vector; and generating a second resulting personality vector of the first NPC based on the base personality vector of the first NPC and the modified second personalized personality vector, wherein the second resulting personality vector of the first NPC influences subsequent interactions between the first NPC and the second UPC [0082-0087] Kerry. In regards to claim 16, Perry in view of Huang and Keller teaches method of claim 1, wherein the plurality of edges of the personality impact graph is associated with a plurality of weights, and wherein a weight of the plurality of weights represents a degree of an impact on the personality vector of the second NPC, based on the interaction between the UPC and the first NPC (fig. 6 (605a-605d) [0067-0074] Keller in view of [0054-0067] Huang. In regards to claim 30, Perry in view of Huang and Keller teaches system of claim 20, wherein the control circuitry is further configured to: based at least in part on the detected interaction, modify the personality vector of the first NPC by adjusting one or more of a plurality of personality traits of the first NPC (fig. 1 10 and interaction with NPC2 and modified parameter) Huang and (fig. 11 friend or foe) Perry. Claim(s) 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Perry et al (2022/0309364) hereinafter, Perry and Huang in view of Zhang (2025/0281836) hereinafter, Zhang. In regards to claim 19, Perry and Huang fail to teach the method of claim 1, further comprising: generating for display on a user interface a plurality of indicators corresponding to a quest object of a plurality of quest objects of the UPC, wherein an indicator of the plurality of indicators shows at least one of: a history of interactions between the UPC and the plurality of NPCs associated with the quest object; interactions between the UPC and the respective NPC of the plurality of NPCs that resulted in a positive impact of the respective personality vector corresponding to the respective NPC; interactions between the UPC and the respective NPC of the plurality of NPCs that resulted in a negative impact of the respective personality vector corresponding to the respective NPC; or impacted relations between the plurality of NPCs based on a plurality of interactions between the UPC and the plurality of NPCs. However, Zhang teaches generating for display on a user interface a plurality of indicators corresponding to a quest object of a plurality of quest objects of the UPC, wherein an indicator of the plurality of indicators shows at least one of: a history of interactions between the UPC and the plurality of NPCs associated with the quest object (fig. 9 you have broken up and reconciled three times); interactions between the UPC and the respective NPC of the plurality of NPCs that resulted in a positive impact of the respective personality vector corresponding to the respective NPC; interactions between the UPC and the respective NPC of the plurality of NPCs that resulted in a negative impact of the respective personality vector corresponding to the respective NPC; or impacted relations between the plurality of NPCs based on a plurality of interactions between the UPC and the plurality of NPCs. PNG media_image8.png 390 446 media_image8.png Greyscale It would have been obvious to one of ordinary skill in the art to modify the teachings of Perry and Huang to further include further comprising: generating for display on a user interface a plurality of indicators corresponding to a quest object of a plurality of quest objects of the UPC, wherein an indicator of the plurality of indicators shows at least one of: a history of interactions between the UPC and the plurality of NPCs associated with the quest object; interactions between the UPC and the respective NPC of the plurality of NPCs that resulted in a positive impact of the respective personality vector corresponding to the respective NPC; interactions between the UPC and the respective NPC of the plurality of NPCs that resulted in a negative impact of the respective personality vector corresponding to the respective NPC; or impacted relations between the plurality of NPCs based on a plurality of interactions between the UPC and the plurality of NPCs as taught by Zhang in order to identity association relationship [101] and higher NPC relatively intelligence.[0005] Claim(s) 2 and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Perry et al (2022/0309364) hereinafter, Perry and Huang in view of Wang et al (20260023772) hereinafter, Wang. In regards to claim 2, Perry and Haung fail to teach the method of claim 1, wherein dynamically causing the second NPC to interact with the UPC comprises generating an input to a large language model (LLM), wherein the input is generated based on the modified personality vector of the second NPC, and wherein the LLM generates, based at least in part on the input, output to be used during the interaction between the UPC and the second NPC. However, Wang teaches wherein dynamically causing the second NPC to interact with the UPC comprises generating an input to a large language model (LLM) [139]. [0139] In another example, a non-player character (NPC) in a video game could be powered by a quantized LLM with a unique personality profile. For example, a grumpy, cynical rogue should consistently respond with sarcasm and self-interest, while a heroic knight should always reply with honor and bravery. If an NPC's personality were to drift over time, this would impair the user experience and make the game less believable. It would have been obvious to one of ordinary skill in the art to modify the teachings of Perry and Haung to further include wherein dynamically causing the second NPC to interact with the UPC comprises generating an input to a large language model (LLM) as taught by Wang in order to make the for a better user experience [139] Therefore, Perry and Haung and Wang teach wherein dynamically causing the second NPC to interact with the UPC comprises generating an input to a large language model (LLM) [139] Wang, wherein the input is generated based on the modified personality vector of the second NPC, and wherein the LLM generates [139] Wang, based at least in part on the input, output to be used during the interaction between the UPC and the second NPC. [0031-0033, 0070-0082] (fig. 4 (420 to 440 to 460)),Perry In regards to claim 21, Perry and Haung in view of Wang teaches, see the rational of claim 2, the system of claim 20, wherein the control circuitry is configured to dynamically cause the second NPC to interact with the UPC by generating an input to a large language model (LLM) [139] Wang,, wherein the input is generated based on the modified personality vector of the second NPC, and wherein the LLM generates, based at least in part on the input, output to be used during the interaction between the UPC and the second NPC[0031-0033, 0070-0082] (fig. 4 (420 to 440 to 460)),Perry. Allowable Subject Matter Claims 5-9, 17-18, 26, 31-32 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. 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 communications from the examiner should be directed to GRANT SITTA whose telephone number is (571)270-1542. The examiner can normally be reached M-F 7:30-4:00. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Patrick Edouard can be reached at 571-272-6084. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /GRANT SITTA/Primary Examiner, Art Unit 2622
Read full office action

Prosecution Timeline

Aug 30, 2024
Application Filed
Apr 15, 2026
Non-Final Rejection mailed — §103
Jul 15, 2026
Response Filed
Sep 15, 2026
Final Rejection mailed — §103 (current)

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Prosecution Projections

3-4
Expected OA Rounds
72%
Grant Probability
86%
With Interview (+13.3%)
3y 0m (~11m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 952 resolved cases by this examiner. Grant probability derived from career allowance rate.

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