Prosecution Insights
Last updated: October 25, 2026
Application No. 18/633,853

SYSTEM AND METHODS FOR ELECTRONIC GAMING CONTROL AND PERFORMANCE NORMALIZATION USING ARTIFICIAL INTELLIGENCE

Non-Final OA §103
Filed
Apr 12, 2024
Examiner
D'AGOSTINO, PAUL ANTHONY
Art Unit
3715
Tech Center
3700 — Mechanical Engineering & Manufacturing
Assignee
Sony Group Corporation
OA Round
3 (Non-Final)
73%
Grant Probability
Favorable
3-4
OA Rounds
8m
Est. Remaining
87%
With Interview

Examiner Intelligence

Grants 73% — above average
73%
Career Allowance Rate
889 granted / 1214 resolved
+3.2% vs TC avg
Moderate +14% lift
Without
With
+13.9%
Interview Lift
resolved cases with interview
Typical timeline
3y 2m
Avg Prosecution
48 currently pending
Career history
1250
Total Applications
across all art units

Statute-Specific Performance

§101
14.2%
-25.8% vs TC avg
§103
40.5%
+0.5% vs TC avg
§102
22.3%
-17.7% vs TC avg
§112
13.0%
-27.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1214 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 . Continued Examination Under 37 CFR 1.114 2. 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 8/24/2026 has been entered. Response to Amendment 3. Applicant has amended the claims and argues that the cited art dose not teach or suggest “wherein the first user performance rating is determined based on a first in-game score of the first user and a second in-game score of the second user during the same game session for the electronic game” (Remarks 8-10 filed 8/24/2026). Examiner disagrees and directs Applicant to the teachings of the skill normalized game of Arnone in the discussion below. Examiner notes a typographical error in Applicant’s remarks (Remarks 8). Examiner did not make the statement that the prior art is silent as to “wherein the first user performance rating is determined based on a first in-game score of the first user and a second in-game score of the second user during the same game session for the electronic game” in the prior Office Action. 4. Applicant’s arguments as to Ng are premised on the amended claim language. Examiner relies on the teachings of Arnone not Ng as to performance ratings based on game scores as discussed below. The rejection of the claims is maintained. 5. Applicant does not offer separate arguments as to the Examiner’s reliance on Pare or Aghdaie for some dependent claims and relies on the amendments and arguments made for the independent claims above. Thus, the rejection of these claims is maintained. Claim Rejections - 35 USC § 103 6. 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 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. 7. 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. 8. The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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. 9. Claims 1-3, 11-13, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Pat. Pub. No. 2016/0082354 to Wakeford in view of U.S. Pat. Pub. No. 2013/0131848 to Arnone. In Reference to Claims 1, 11, and 20 Wakeford discloses a device (Fig. 1 server 102) for electronic gaming control and normalization, comprising: an interface (Fig. 1 server 102 is an interface between game (Fig. 1 game module 106) streaming over network [0002, 0007, 0017] and client computing platform 104); a memory storing executable instructions (Fig. 1 storage 118 and instructions [0003, 0004, 0033-0034]); a controller (Fig. 1 processor 120) coupled to the interface and the memory (Fig. 1), therein the controller is configured to carry out the steps (Fig. 2), comprising: receiving, by the device, a first game data stream for an electronic game and a second game data stream for the electronic game, wherein the first game data stream includes game data for a first user of the electronic game executed on a first user device and the second game data stream includes game data for a second user of the electronic game executed on a second user device (multiple clients receive individual data streams of game data of a same game where “system 100 may include one or more servers102. The server 102 may be configured to communicate with one or more client computing platforms 104 according to a client/server architecture. The users may access system 100 and/or the virtual space via client computing platforms 104, for instance, to engage in one or more games.” [0014]. And “[t]he game may be provided via a virtual space, and may include a plurality of resource types and/or maps. An instance of the virtual space may be executed by computer modules to determine views of the virtual space. The views may then be communicated (e.g., via streaming, via object/position data, and/or other information) from server(s) 102 and/or sources to client computing platforms 104 for presentation to users.” [0017] for “a virtual game that may provide more engaging and immersive in-game experiences.” ([0013]), wherein the first game data stream and the second game data stream are generated during a same game session for the electronic game (users engage in one game comprising game data [0014, 0018-0021] where “[t]he game module 106 may be configured to execute an instance of a game to facilitate presentation of the game to users. The game module 106 may be configured to implement in-game actions in the instance of the game, in response to action requests for the in-game actions by the users.” [0016]); determining, by the device, a first device capability associated with the first user device using the first game data stream and a second device capability associated with the second user device using the second game data stream (Fig. 1 user resource determination module 108 wherein “capabilities available to users in connection with game play to include, without limitation, computing resources, network connectivity and game controller functionality, are detected, and various game characteristics relating to the difficulty of game play may be adjusted based on this information. Accordingly, embodiments may be configured for detection of hardware parameters such as device type being used, computing resources available on the device being used, characteristics of the display being used for game play and/or characteristics of one or more interface devices being used for gameplay.” [0013]); and controlling, by the device, output of the first game data stream using the customization {normalization} setting for the first user (Fig. 2 206 and 208 wherein a user resource parameter is associated with a difficulty customization of a user in connection with the play of the player [0027, 0028, 0041] and the playing field for game players “may be leveled as between players that have a substantial difference in the capabilities of hardware and/or network available to them. As a result, users with more limited capabilities can be more competitive in head-to-head game play and are more likely to participate in various games that they otherwise might not due to the inferiority of their hardware and/or network resources as compared to other players.” [0044]). However, Wakeford is silent as to: determining, by the device, a first user performance rating for the first user and a second user performance rating for the second user based on a first user ability of the first user and a second user ability of the second user; wherein the first user performance rating is determined based on a first in-game score of the first user and a second in-game score of the second user during the same game session for the electronic game; and determining, by the device, a normalization setting for the first user of the electronic game based on the first user performance rating, the second user performance rating, and a determined difference between the first device capability and the second device capability, the normalization setting modifying at least one game operation of the electronic game. One of skill in the art would be aware of the skill normalization in games of Arnone to ensure fair play among players (Abstr.). According to the system and method of Arnone, his invention employs a skill normalization module that incorporates handicaps to a game world engine that configures the game world engine to implement each assigned handicap within a normalized game (Abstr.). In particular, the normalization module (Fig. 1A 126), determines a first user performance rating for the first user (Fig. 2 player 1 ranking 208, Fig. 3A 304) and a second user performance rating for the second user (Fig. 2 player 2 ranking 208, Fig. 3A 302) based on a first user ability of the first user (Fig. 2 player 1 performance measurements 206, Fig. 3A 306) and a second user ability of the second user (Fig. 2 player N performance measurements 206, Fig. 3A 308 for each player); wherein the first user performance rating is determined based on a first in-game score of the first user and a second in-game score of the second user during the same game session for the electronic game (performance or player’s results “score” [0045], at the outcome or any intermediate point such as the end of a quarter [0053], compute score and handicap across multiple devices [0059], communicating performance and scores of players in a tournament [0065]), and determines, by the normalization module, a normalization setting (According to Applicant, “[t]he normalization setting may remove a player from a game or handicap the player by making it more difficult for that player so that their play level using the bot is balanced with the play of other players not using a bot.” [0059]. Reading this limitation in light of Applicant’s Specification, a normalization setting can be a handicap setting or a setting based on handicaps stemming from player performance, scores and ramnkings.)(See Arnone Fig. 2 handicap 218 and implement handicap 220, see also apply handicap [0053] to make handicap assignments [0070] assigning handicaps where there is a relative difference between players [0073-0074]) for the first user of the electronic game based on the first user performance rating (Fig. 2 218), the second user performance rating (Fig, 2 218 for each of N players), and a determined difference between the first device capability and the second device capability (difference [0073], the normalization setting modifying at least one game operation of the electronic game and controlling the game output based on the settings (Arnone teaches of numerous settings tuned to advantage low skill players [0089] and disadvantage high skill players [0090]. Specifically, “[i]n several embodiments, utilization of a skill normalization module can provide advantages to low skill player(s) in order to provide fair game play irrespective of player skill. These advantages may consist of (but are not limited to) access to better equipment, advantages in timing, extra moves, better starting position, relative scoring, or a variety of other mechanisms. For instance, a low skill player may pick up night vision goggles to provide higher visibility in a shooter game, or better armor in a sword fighting game. In a racing game, the low skill player may be granted a head start at the start of the race. In a turn based game, the low skill player may gain additional opportunities to attack an opponent. In a fighting game, the player may have increased health at the start of gameplay. In a foosball game, the player may get two points for each goal scored rather than a single point. These advantages may dynamically change as a result of gameplay.” [0089]. In numerous embodiments, utilization of a skill normalization module can disadvantage more skilled player(s) in order to provide fair game play irrespective of player skill. These disadvantages can occur through (but are not limited to) introducing a random element or element(s) into the game, changing the player's options, relative scoring, or adjusting overall score at the end of gameplay. In a shooting game, for example, the accuracy with which shots can be aimed at targets can be a function of the aim of the player plus a random component that impacts the trajectory of the player's shot. For a more skilled player, the random component may be increased, decreasing the effect of the player's skill. In a racing game, the cars available to more skilled players may break down more readily. In a shooting game, the more skilled player may not be able to use certain guns or other weaponry. In a basketball shooting game, the player's baskets may be worth 1 point instead of two points.” [0090]. The Supreme Court in KSR Int'l Co. v. Teleflex Inc., 550 U.S. 398, 415-421, 82 USPQ2d 1385, 1395-97 (2007) identified a number of rationales to support a conclusion of obviousness (A) Combining prior art elements according to known methods to yield predictable results; (B) Simple substitution of one known element for another to obtain predictable results; (C) Use of known technique to improve similar devices (methods, or products) in the same way; and (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results. Here, one of skill in the art would modify the hardware parameters and game customizations of Wakeford who is trying to compensate for players that have a substantial difference in the capabilities with the normalization module and affect on player game settings of Arnone to achieve the predictable result of providing fair game play irrespective of player skill for low skill and high skill players. The Courts have held that combining prior art elements according to known methods to yield predictable results to be indicia of obviousness. In Reference to Claims 2 and 12 Wakeford discloses hardware differences (“hardware configuration and/or network connectivity capabilities” [0003, 0006], “device type being used” [0013]) and control input differences (“characteristics of one or more interface devices being used for gameplay” [0013, 0023], “controller type, mouse, keyboard, touch screen” [0024]). In Reference to Claims 3 and 13 Wakeford discloses tracking streams over a period of time to detect latency wherein his assessment occur on a periodic basis as, for example, “network capabilities such as latency and response time vary over time.” ([0027]) as to a specific player hardware configuration and device type ([0003, 0006, 0013, 0023-0024]). 10. Claims 4, 8-10, 14, and 18-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wakeford, Arnone, further in view of WO 2021/202396 to Pare. In Reference to Claims 4 and 14 Wakeford discloses the invention substantially as claimed. However, the reference does not explicitly disclose using a machine model to determine at least one normalization parameter for modification of a game function, the machine model trained to identify network lag. One of skill in the art would be aware of the network of Pare. According to Pare, "an incoming game streaming request 1028 may be associated with player attributes that indicate a player 112 associated with the game streaming request 1028 has played an above-threshold number (e.g., over 1000) of games within a period of time (e.g., within the past 6 months). In this example, the streaming instance assignment algorithm 215 - using a rule-based approach, a machine-learning model(s), etc. - might determine a relatively - high value 238 for this game streaming request 1028 in order to assign, to the game streaming request 1028, a VM instance 1026 that can provide relatively -high performance (e.g., low latency, or an otherwise "snappy" streaming experience) to the client device 114 of the player 112 of the game streaming request." [0132]. Pare teaches this process in order to provide a low latency gaming experience {normalization parameter}. Conversely, Pare teaches, based on player attributes, to offer a higher latency to deliver lower costs to subscribers [0132]. Additionally, in other instances, Pare assesses attributes to allow streaming to more client devices 114 using a single server; to lower cost to a subscriber for streaming; and thereby provide a cost savings to the developer [0132]. Here, it would require only routine skill in the art to modify the streaming of Wakeford with the machine model based on user attributes to deliver low or high latency tuned to the user performance to have either "snappy" game experiences or lower costs gaming. The Courts have held that combining prior art elements according to known methods to yield predictable results to be indicia of obviousness. In Reference to Claims 8 and 18 Pare teaches of modification of network lag ([0132]). In Reference to Claims 9 and 19 Pare teaches of modification of the streaming to allow high performance client devices to play for a snappy experience which is a reduced hardware lag of at least one user ([0132]). In Reference to Claim 10 Pare teaches of updating a machine model for normalization based on the analysis of user performance for the first user after application of the normalization setting ([0132]). 11. Claims 5-7 and 15-17 are rejected under 35 U.S.C. 103 as being unpatentable over Wakeford, Ng, further in view of U.S. Pat. Pub. No. 2017/0259177 to Aghdaie. In Reference to Claims 5 and 15 Wakeford discloses the invention substantially as claimed and Arnone discloses determining a performance rating for the at least one user includes determining at least one reaction time measurement for the at least one user relative to electronic game (Arnone [0089, 0090]). However, the reference does not explicitly disclose using the normalization setting comprises modifying an appearance of at least one game object by altering a size of a portion of the at least one game object. One of skill in the art would recognize the dynamic difficulty adjustments of Aghdaie. Aghdaie teaches of adjusting the difficulty settings for the video game may include “changing configuration values that adjust a defined set of features in the video game 112. Alternatively, the difficulty configuration system 132 may determine configuration settings based at least in part on an evaluation of specific skills of the user as determined from the recent user interaction data. For example, it may be determined that the user is failing a number of objectives in the video game 112 because the user has trouble timing jumps. If the user is a type of user who will stop playing a video game 112 when the user has trouble completing objectives, as determined by the user cluster associated with the user, the difficult configuration system 132 may generate configuration values for the capabilities of the playable character in the video game 112 to make it easier to time the jumps (for example, by allowing the character to jump farther). In contrast, if another user does not have a problem timing jumps, but has trouble aiming a weapon, the difficulty configuration system 132 may generate configuration values that make it easier to shoot objectives by making the hit area of a weapon larger. In some cases, both of these changes may be made without the users realizing that the game has been modified.” [0116]). Here, it would require only routine skill in the art to modify the customizations of hardware and software {normalizations} of Wakeford with the making of hit areas larger to adjust a difficulty configuration for a user of a game of Aghdaie. The Courts have held that the use of a known technique to improve similar devices (methods, or products) in the same way to be indicia of obviousness. In Reference to Claims 6 and 16 Further, Aghdaie teaches of controlling speed of movement of a game character wherein “[s]ome other non-limiting examples of features of the video game that can be modified, which may or may not be detectable by the user can include providing extra speed to an in-game character, improving throwing accuracy of an in-game character, improving the distance or height that the in-game character can jump, adjusting the responsiveness of controls, and the like. In some cases, the adjustments may additionally or alternatively include reducing the ability of an in-game character rather than improving the ability of the in-game character. For example, the in-game character may be made faster, but have less shooting accuracy.” ([0034]). In Reference to Claims 7 and 17 Aghdaie teaches of reducing constraints for completing a game function wherein “the difficult configuration system 132 may generate configuration values for the capabilities of the playable character in the video game 112 to make it easier to time the jumps (for example, by allowing the character to jump farther.” ([0116]). Conclusion 12. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure is in the Notice of References Cited. 13. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Paul A. D’Agostino whose telephone number is (571) 270-1992. 14. Examiner interviews may be available depending on the stage of prosecution and provided 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. 15. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kang Hu can be reached on (571) 270-1344. The fax phone number for the organization where this application or proceeding is assigned is 571-270-2992. /PAUL A D'AGOSTINO/Primary Examiner, Art Unit 3715
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Prosecution Timeline

Show 1 earlier event
Feb 19, 2026
Non-Final Rejection mailed — §103
May 12, 2026
Applicant Interview (Telephonic)
May 12, 2026
Examiner Interview Summary
May 19, 2026
Response Filed
Jun 12, 2026
Final Rejection mailed — §103
Aug 24, 2026
Request for Continued Examination
Aug 27, 2026
Response after Non-Final Action
Oct 06, 2026
Non-Final Rejection mailed — §103 (current)

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Prosecution Projections

3-4
Expected OA Rounds
73%
Grant Probability
87%
With Interview (+13.9%)
3y 2m (~8m remaining)
Median Time to Grant
High
PTA Risk
Based on 1214 resolved cases by this examiner. Grant probability derived from career allowance rate.

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