DETAILED ACTION
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 .
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.
Response to Amendment
It is noted that claims 1-21 have been amended in the response filed on 5/20/2026.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 5 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 5 recites “each of the additional minigames is automatically identified said each of the additional minigames…” This portion of the claim appears grammatically incorrect starting with “said each of”. It is unclear what the intention was after the additional minigames is automatically identified.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Is the Claim to a Process, Machine, Manufacture or Composition of Matter?
Claims 1-21 recite a series of steps for controlling a computer applied to a game system. Thus, these claims are to a process, which is one of the statutory categories of invention.
Step 2A: Prong One: Does the Claim Recite an Abstract Idea?
Claim 1 recites”
A method, comprising:
detecting, during an active game session of a video game, that a video game training option presented on a user interface has been selected; in response to detecting that the video game training option has been selected:
pausing the active game session of the video game; and
generating, using a trained machine learning model, a plurality of minigames, wherein the plurality of minigames are generated by:
providing past game inputs from one or more prior gameplay sessions and current game inputs from the active game session to the trained machine learning model;
in response to the providing, receiving, from the trained machine learning model, outputs indicative of skill levels of the user with respect to the video game;
and using the outputs to identify one or more video game code segments of the video game, wherein each video game code segment of the one or more video game code segments corresponds to a skill level of the skill levels of the user;
causing information representing the plurality of minigames to be presented on the user interface;
in response to causing the information to be presented, detecting that a minigame from the plurality of minigames has been selected;
in response to detecting that the minigame has been selected, executing a video game code segment of the one or more video game code segments, the video game code segment associated with the minigame, wherein executing the video game code segment causes a portion of the video game associated with the video game code segment to be presented on the user interface;
and after executing the video game code segment, resuming the active game session of the video game.
The examiner finds that the foregoing underlined elements recite 1) a certain methods of organizing human activity because they describe managing personal behavior or relationships or interactions between people (including social activities, and following rules or instructions, i.e. game rules, or teaching instructions). In the instant application, the claim is directed to merely detection of inputs in a video game, suggesting/generating minigames to improve skills of the user playing the minigames, i.e. thereby following game rules or instructions being provided. The claim language equates to detecting that someone is not good at an activity, i.e. sport or educational topic, offering them training or tutoring, stopping their current activity, placing them in a remedial session where additional training materials are provided to them based on their skill level detected and then once they have finished practicing the skill, the person is rejoined into the regular activity.
Step 2A: Prong Two: Does the Claim Recite Additional Elements That Integrate The Abstract Idea Into a Practical Application?
The elements that are not underlined and bolded above are the additional elements.
The examiner finds that each of the following additional elements merely recites the words “apply it” (or an equivalent) with the abstract idea, or merely includes instructions to implement the abstract idea on a computer, or merely uses a computer as a tool to perform the abstract idea. Generation and execution of code segments are merely taking the abstract concept of providing remedial training opportunities to someone and applying it to the video game environment using the computer as a tool. Nothing in the claim language improves the functioning of the computer itself or improves gaming technology.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. For example, there is no indication that the combination of elements improves the functioning of a computer or improves any other technology.
The dependent claims and independent claims 19 and 21 merely include limitations that either further define the abstract idea (and thus don’t make the abstract idea any less abstract) or amount to no more than instructions to implement the abstract idea on a computer, or use a computer as tool to perform the abstract idea. Taken alone, the additional elements do not integrate the abstract idea into a practical application. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. For example, there is no indication that the combination of elements improves the functioning of a computer or improves any other technology.
Step 2B: Does the Claim Recite Additional Elements That Amount to Significantly More Than the Abstract Idea?
The examiner finds that the additional elements do not amount to significantly more than the abstract idea for the same reasons discussed above with respect to the conclusion that the additional elements do not integrate the abstract idea into a practical application.
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.
Claim(s) 1-8, 10-17, 19 and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fortuna (US 11,524,240 B1) in view of Krishnamurthy (US 2017/028063 A1).
Regarding claims 1, 19 and 21, Fortuna discloses a method, system and non-transitory computer readable medium comprising the processing steps of: detecting during an active game session of a video game, that a video game training option presented on a user interface of a client device has been selected (Fortuna Figs. 3 & 8, col. 1 lines 60-64, col. 10 lines 10-19, 61-67, col. 11 lines 1-14, i.e. a user may select to engage in training activities during game play)
pausing the active game session of the video game (Fortuna col. 10 lines 13-15)
generating a plurality of minigames (Fortuna col. 10 lines 20-27, 61-67, col. 11 lines 1-14, i.e. the practice scenarios and training activities are considered minigames)
the plurality of minigames are generated/suggested by:
providing past game inputs from one or more prior gameplay sessions and current game inputs from the active game session to the data system (Fortuna col. 4 lines 36-37, col. 6 lines 3-22, the training materials are is analyzed to determine if a player is struggling at a particular point in the game and are customized and filtered based on current and historical data current gameplay data ),
in response to the providing, receiving from the system outputs indicative of skill levels of the user with respect to the video game (Fortuna col. 4 lines 17-38, customized training is provided based on player skill level)
using the outputs to identify one or more video game code segments of the video game, wherein each video game code segment of the one or more video game code segments corresponds to a skill level of the skill level of the user (Fortuna col. 4 lines 17-38, once the skill level is determined for the player the game customizes training opportunities for the user based on skill level)
causing information representing the plurality of minigames to be presented on the user interface (Fortuna Fig. 3 & 8, col. 10 lines 24-39 i.e. a plurality of different training options are presented to the player)
in response to causing the information to be presented, detecting that a minigame from the plurality of minigames has been selected (Fortuna Figs. 3 & 8, col. 1 lines 60-64, col. 10 lines 61-67, col. 11 lines 1-14)
responsive to detecting that the minigame has been selected, executing a video game code segment of the one or more video game code segments, the video game code segment associated with the minigame, wherein executing the video game code segment causes a portion of the video game associated with the video game code segment to be presented on the user interface; and (Fortuna , once a training has been selected it is executed on the game play device)
after executing the video game code segment, resuming the active game session of the video game (Fortuna, Fig. 5, col. 13 lines 40-56, after executing the training options the user may resume game play from the pause menu).
While Fortuna discloses aggregating the current and historical game play data using data models to generate training for players (Fortuna col. 4 lines 53-54), Fortuna lacks in specifically disclosing using a trained machine learning model to adaptively generate the minigames. Krishnamurthy teaches of a personalized game training system in which a trained learning model (#510) is used to generate a plurality of personalized mini-games (Krishnamurthy Fig. 5, adaptive agent trainings are mini-games). Kristhnamurthy’s system provides past game inputs from one or more prior gameplay sessions (#530) and current game inputs (#540) to determine and output a skill level of a user (Krishnamurthy Fig. 5, #512). Once a player’s skill level is determined, one or more video game code segments of the video game are identified, wherein each video game code segment of the one or more video game code segments correspond to a skill level of the skill levels of the user (Krishnamurthy Fig. 3, Fig. 7, ¶0026, ¶0027, ¶0039-¶0044, ¶0056, the trained machine learning model determines the player’s skill level, when the player needs assistance in the game, an adaptive agent (i.e. can be considered to be a training session or mini-game/practice) is generated (i.e. video game code segments) to help train the player on various skills). It would have been obvious to one of ordinary skill in the art at the time the invention was filed to use the trained machine learning model with the generation of an adaptive agent in Krishnamurthy to select the customized training for a player in the game system of Fortuna. By using the machine learning model and adaptive agent, the training curriculum provided by Fortuna can be dynamic and generated using the machine learning model, thereby adjusting according to a player’s need for training.
Regarding claim 2, Fortuna further discloses, presenting an option for resuming the active game session, the option provided upon detecting the user has acquired at least a predefined amount of a distinct set of input skills associated with the minigame (col. 12 lines 30-42).
Regarding claim 3, Fortuna discloses wherein the option for resuming the active game session includes a first option to begin the video game from a resumption point, wherein the resumption point is defined by the user or is determined from the one or more prior gameplay sessions of the user for the video game, and wherein the resumption point is identified to be a point where the user stopped the active game session or where the user had difficulty in progressing in the video game (Fortuna col. 12 lines 30-40).
Fortuna lacks in specifically disclosing an option to start game play from the beginning of the game. It would have been obvious to one of ordinary skill in the art at the time the invention was filed to allow players to start the game back at the beginning of the game once they have completed minigame training sessions. By starting at the beginning of the game, the player can then see if they can improve their score and move forward in the game with the new skills they have learned.
Regarding claim 4, Fortuna further discloses, tracking progress of the user during execution of the video game code segment, the tracking performed by analyzing inputs provided by the user during the current execution, the analyzing of inputs used to determine a level of difficulty experienced by the user in successfully completing the minigame; and dynamically identifying and causing additional minigames to be presented as updates to the user interface, the additional minigames identified to adapt to the level of difficulty experience by the user, the additional minigames are specific to the user and the minigame (Fortuna col. 11 lines 52-59).
Regarding claim 5, Fortuna further discloses, wherein each of the additional minigames is identified automatically or is identified based on minigame-selection inputs provided by the user, and wherein the minigame-selection inputs define complexity of skills desired by the user for practicing, and each of the additional minigames is automatically identified said each of the additional minigames based on said minigame-selection inputs of the user (Fortuna col 10 lines 61-67, col. 11-16, 52-59).
Regarding claim 6, Fortuna further discloses, wherein each of the additional minigames is generated and presented on the user interface for user selection in substantial real-time, based on the progress made in the minigame (Fortuna col. 4 lines 27-29, col. 11 lines 52-59).
Regarding claim 7, Fortuna further discloses, wherein each of the additional minigames is identified to include a select portion of the video game that requires certain ones of basic input skills required to successfully attempt a distinct set of input skills of the minigame, said each of the additional minigames for acquiring said certain ones of the basic input skills identified based on the level of difficulty experienced by the user during execution of the video game code segment (Fortuna col. 7 lines 15-67, col. 8 lines 1-57).
Regarding claim 8, Fortuna further discloses, wherein each of the additional minigames is identified to include a select portion of the video game that requires certain ones of advanced input skills the user desires to acquire for progressing in the video game, said each of the additional minigames for acquiring said certain ones of the advanced input skills identified based on input skills exhibited by the user during execution of the video game code segment (Fortuna col. 9 lines 38-64).
Regarding claim 10, Fortuna discloses, monitoring inputs from the user during execution of the video game code segment by providing real-time feedback to the user, the real-time feedback provided as any one of a textual suggestion, a verbal suggestion, visual input tips or haptic input tips or audio input tips using user interface elements, timing indicators, and screen prompts, and wherein the portion of the video game associated with each of the plurality of minigames corresponds to a storyline of the video game that is non-linear (Fortuna Fig. 4, col. 11 lines 60-67; col. 12 lines 1-14).
Regarding claim 11, Fortuna discloses, wherein each minigame of the plurality of minigames includes a tutorial option, which when activated by a selection option provided on the user interface, provides guidance to the user for providing game inputs required for progressing in the portion of the video game associated with said each minigame, the tutorial option provided in a textual or a visual or an audio or a haptic guidance format (Fortuna Fig. 4, Fig. 5 #530).
Regarding claim 12, Fortuna discloses that the user can pause gameplay and enter the tutorial curriculum and then may resume gameplay (col. 12 lines 30-42). Fortuna does not explicitly mention generating guardrails for the portion of the video game, the guardrails identified to prevent exposing the user to other portions of the video game that are beyond a resumption point, wherein the resumption point is a point in the video game where the active game session was paused. However, it implicit in Fortuna and would have been obvious to one skilled in the art at the time of filing that the tutorial curriculum of Fortuna may have “guardrails” not allowing players to move beyond the point in the game from which it was paused. The tutorial curriculum of Fortuna is to assist users in increasing their skill level based on game play that has already occurred and evaluating which portions of the game they player is struggling with. It would have been obvious to not allow a player to select or move further in a game beyond where their game play was already paused, as that would give a player an advantage in the game and spoil what is to come in game play.
Regarding claim 13, Fortuna discloses, wherein the portion of the video game associated with each minigame of the plurality of minigames is identified as a portion that the user previously attempted during the one or more prior gameplay session (Fortuna col. 9 lines 8-29).
Regarding claim 14, Fortuna discloses, presenting a visual representation of progress made by the user on the user interface during execution of the video game code segment (Fortuna Fig. 10 #1030).
Regarding claim 15, Fortuna discloses, wherein each minigame of the plurality of minigames is generated by taking into consideration characteristics of a character used for representing the user in the video game, the characteristics identifying a type of input skills exhibited by the character in the gameplay of the video game during the one or more prior gameplay sessions, and said each minigame is generated to improve the type of input skills exhibited by the character representing the user (col. 7 lines 1-14, col. 11 lines 60-67, col. 12 lines 1-14).
Regarding claim 16, Fortuna discloses, wherein the video game training option is provided to the user based on evaluation of input skills retrieved from the one or more prior gameplay sessions of the user and one or more of other users who have played the video game (col. 2 lines 58-67, col. 9 lines 28-41).
Regarding claim 17, Krishnamurthy teaches, the trained machine learning model is built and trained using input skills of the user identified and extracted from the one or more prior game play sessions and a game state of the video game (Krishnamurthy Fig. 5 ¶0053). As stated with respect to claim 1, it is obvious to incorporate Krishnamurthy’s trained learning model as the data model of Fortuna.
Claim(s) 9, 18 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fortuna in view of Krishnamurthy as applied to claim 1 above, and further in view of Arezina US 2012/0157193.
Regarding claim 9 and 20, Fortuna discloses selection of minigames by the user through a screen selection button (Fig. 5) which are used to build the input skills of the user necessary for progressing in the video game in a linear manner, and wherein the portion of the video game associated with the corresponding minigame includes a key event of the video game (Fig. 8, col. 9 lines 8-29). Fortuna lacks in disclosing thumbnails. Arezina teaches of a gaming system in which the information representing the plurality of minigames are presented as thumbnails in a sandbox for selection by the user, the sandbox allowing a non-linear selection of any one of the thumbnails for accessing and practicing a corresponding portion of the video game associated with the corresponding minigame (Arezina ¶ 150). It would have been obvious to one of skill in the art at the time of filing of the invention to use thumbnails to display available minigames. Thumbnails provide an easy selection and display for users to select.
Regarding claim 18, Fortuna discloses a display of distinct key event that can be achieved with the input skills required by the user to progress in the video game (Fig. 8). Fortuna lacks in disclosing thumbnails presented to include an image representation of the distinct key event associated with said each thumbnail. Arezina teaches of a gaming system in which the information representing a plurality of minigames are presented as thumbnails depicting image representation of distinct key events associated with the thumbnail (i.e. what the thumbnail refers to) (Arezina ¶ 150). It would have been obvious to one of skill in the art at the time of filing of the invention to use thumbnails to display available minigames. Thumbnails provide an easy and visual selection and display for users to select.
Response to Arguments
Applicant's arguments filed May 20, 2026 with respect to the 35 USC 101 rejection have been fully considered but they are not persuasive.
Applicant argues that the claims are not directed to a mental process or methods of organizing human activity and instead are directed to a computer-centric workflow. The examiner notes that the claims do require a computer to be performed. However, the claims are merely using the computer as a tool to perform training steps in a video game environment. Applicant argues that since the claims recite “pausing the active game session”, utilizing a trained machine learning model to “identify one or more video game code segments,” “executing a video game code segment,” and “resuming the active game session” the claims do not manage human behavior but are directed to managing computer system operations. The examiner disagrees and notes that the claims are managing human behavior. For example, the claims can be said to equate to 1) Detect that a person needs additional assistance in what they are doing, so stop playing a sport or doing your math homework, i.e. pausing an activity. 2) Create customized training for the person, i.e. training drills in sports or specific math practice problems. 3) Resume the regular activity once they have practiced skills for a while. This is common training, i.e. following rules or instructions, which is considered organizing human activity.
Applicant further argues that the claims are integrated in a practical application by being directed to a specific technological solution of a technical challenge of integrating training into a video game without permanently interrupting or abandoning the ongoing game. The examiner disagrees and notes that it is common to pause video games or portions thereof, complete training activities and then go back to the main game as noted in the prior art. Applicant has not provided any evidence that this has been a technical challenge in the video game art that they have created the solution for.
Applicant further argues that the claim elements, evaluated both individually and as an ordered combination, add significantly more to the alleged abstract ideas and recite a patent-eligible invention. The examiner notes there is no additional elements beyond a generic computer and therefore does not amount to significantly more.
Applicant’s arguments with respect to the 35 USC 102 rejection of claim(s) 1-21 have been considered but are moot in view of the new ground of rejection.
Applicant argues that Fortuna lacks in disclosing the specific state-management process and machine learning architecture recited in the claims including dynamically analyzing past game inputs to identify video code segments corresponding to a user’s skill. The examiner disagrees and notes that Fortuna does look at examiner’s past play history as well as the current game state to determine which trainings to suggest to players as noted above. Nevertheless, the examiner has amended the rejection due to the amended claim language to incorporate Krishnamurthy which uses a machine learning model to determine the player’s skill level based on past game inputs as well as current game inputs (Krishnamurthy Fig. 5). Krishnamurthy then uses the skill level determined to develop dynamic training for the player. For example, the adaptive agent is used herein the system dynamically creates video code game segments to dynamically train the player in the video game adjusting to the player’s skill level.
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 JULIE K BROCKETTI whose telephone number is (571) 272- 0206. The examiner can normally be reached M-Th 8:00 a.m. - 5:00 p.m..
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Thomas Barrett can be reached at 571-272-4746. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JULIE K BROCKETTI/ Primary Examiner, Art Unit 3700
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