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 .
Status of Claims
In response to the Preliminary Amendment filed on June 10th, 2024, claims 21-50 have been cancelled. Claims 1-20 are currently pending.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-6, 9, 10, 11-16, 19, and 20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Anderson (US 2018/0361254 A1).
Regarding claims 1 and 11, Anderson discloses a method for modulating dynamics of multiuser events, the method comprising:
monitoring, while a multiuser event is ongoing, an actual performance dynamics (APD) score associated with avatars participating in the multiuser event (see par. [0024], Referring to FIG. 2, in certain examples, a method 200 of controlling user success in the online game can involve monitoring a success rate for a user or group of users);
determining that a difference between the APD score associated with the avatars participating in the multiuser event and a set performance dynamics (SPD) score is outside of a threshold (see par. [0026], For example, when the user's actual success rate exceeds the target success rate, the game can be made more difficult for the user, to decrease the actual success rate closer to the target success rate); and
based on the difference between the APD score and the SPD score being outside of the threshold, modulating at least one subset of avatars participating in the multiuser event to cause a reduction in the difference between the APD score and the SPD score (see par. [0026], For example, when the user's actual success rate exceeds the target success rate, the game can be made more difficult for the user, to decrease the actual success rate closer to the target success rate; also see par. [0028], In some examples, the difficulty of the online game can be adjusted by changing one or more game play parameters. The game play parameters can include or define, for example…a capability of a user or the user's avatar in a virtual environment).
Regarding claims 2 and 12, Anderson discloses wherein the monitoring the APD score associated with the avatars participating in the multiuser event comprises determining the APD score associated with the avatars participating in the multiuser event at a time point of the multiuser event, the time point being based on at least one of: an avatar that stops participating in the multiuser event; a change in the multiuser event; or a set time increment (see par. [0025], Next, the success rate for the user in the online game can be monitored (step 210) over time, for example, based on a rate (e.g., in time) of advancement or achievement in the online game. Such advancement or achievement can include, for example, advancing to a certain game level (e.g., level 5 or level 10), achieving a certain score, defeating one or more competitors, and/or acquiring one or more virtual items or objects).
Regarding claims 3 and 13, Anderson discloses wherein the determining the APD score associated with the avatars participating in the multiuser event comprises determining, at the time point, individual actual performance dynamics (IAPD) scores, each IAPD score relating to an avatar participating in the multiuser event (see par. [0025], Next, the success rate for the user in the online game can be monitored (step 210) over time, for example, based on a rate (e.g., in time) of advancement or achievement in the online game. Such advancement or achievement can include, for example, advancing to a certain game level (e.g., level 5 or level 10), achieving a certain score, defeating one or more competitors, and/or acquiring one or more virtual items or objects).
Regarding claims 4 and 14, Anderson discloses wherein the modulating the at least one subset of avatars participating in the multiuser event comprises selecting an avatar that is not currently participating in the multiuser event for inclusion into the at least one subset of avatars participating in the multiuser event, wherein the selecting is based on an individual historical performance dynamics (IHPD) score of the avatar that is not currently participating in the multiuser event (see par. [0028], In some examples, the difficulty of the online game can be adjusted by changing one or more game play parameters. The game play parameters can include or define, for example…a frequency and/or intensity of obstacles or challenges (e.g., encounters with other competitors); Anderson’s success rate would define a IHPD score because the player character’s success rate versus a competitor character would conversely define the competitor character’s success rate against the player’s character).
Regarding claims 5 and 15, Anderson discloses wherein the modulating the at least one subset of avatars participating in the multiuser event comprises selecting an avatar from the at least one subset of avatars based on an IAPD score of the avatar; and modulating the participation of the selected avatar in the multiuser event; or modulating the IAPD score of the selected avatar (see par. [0028], Additionally or alternatively, the difficulty can be adjusted by changing a value, a strength, a power, and/or an effectiveness of virtual characters or virtual items. For example, the difficulty can be increased by making a user's avatar slower or weaker and/or by making a user's virtual weapon (e.g., a virtual gun) or defenses (e.g., a virtual wall) less effective).
Regarding claims 6 and 16, Anderson discloses wherein the modulating the IAPD score of the selected avatar comprises determining a skill score contributing to the selected avatar's IAPD score; and modulating the skill score of the selected avatar (see par. [0028], Additionally or alternatively, the difficulty can be adjusted by changing a value, a strength, a power, and/or an effectiveness of virtual characters or virtual items. For example, the difficulty can be increased by making a user's avatar slower or weaker and/or by making a user's virtual weapon (e.g., a virtual gun) or defenses (e.g., a virtual wall) less effective).
Regarding claims 9 and 19, Anderson discloses wherein the APD score is based on individual actual performance dynamics (IAPD) scores associated with respective subsets of avatars participating in the multiuser event (see par. [0025], Alternatively or additionally, the user can be assigned to a group of users who selected the offer and/or have an identical or similar installation history. In that case, the success rate for the user and other users in the group can be, for example, an average, a median, a minimum, or a maximum success rate for the users); and each IAPD score of an avatar is based at least on a beneficial action and/or a detrimental action performed by the avatar (see par. [0025], Next, the success rate for the user in the online game can be monitored (step 210) over time, for example, based on a rate (e.g., in time) of advancement or achievement in the online game. Such advancement or achievement can include, for example, advancing to a certain game level (e.g., level 5 or level 10), achieving a certain score, defeating one or more competitors, and/or acquiring one or more virtual items or objects).
Regarding claims 10 and 20, Anderson discloses wherein the SPD score is based on individual historical performance dynamics (IHPD) scores associated with respective subsets of avatars participating in the multiuser event (see par. [0027], In some instances, the target success rate can be defined or determined (e.g., by a developer or manager of the online game) in an effort to optimize game enjoyment, improve competitiveness, and/or manage expenses. The target success rate can, in certain examples, be associated with the user and any similar users who arrived at the online game by selecting the offer. Other users, who arrived at the online game through a different route (e.g., a different offer), can have a different target success rate and/or can be monitored separately; also see par. [0021], Such information can be or include, for example, a history of user connections to and/or interactions with the online game and/or the system 100, a history of content presented to users, user installations, user purchases, user accomplishments, user tasks, and/or user interactions with other users (e.g., group chats)).
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.
The factual inquiries 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 7 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Anderson (US 2018/0361254 A1) in view of NPL document “Examining Game Pace: How Single-Player Levels Tick” (hereinafter referred to as Game Pace).
Regarding claims 7 and 17, Anderson discloses the method as discussed above. However, Anderson does not explicitly disclose wherein the SPD score is based on an SPD curve defined by a set of predefined SPD values as function of time points of the multiuser event.
Game Pace teaches game level pacing and a difficulty curve wherein the SPD score is based on an SPD curve defined by a set of predefined SPD values as function of time points of the multiuser event (see figure on pg. 7 and pg. 7, 3rd par., A general battle against a group of enemies in a game tends to follow a bell-curve pattern; also see pg. 7, 4th par., For example, a Left 4 Dead horde encounter follows this pattern -- the initial build up of enemies increased fairly rapidly up to a maximum number and a frantic tempo, before the player manages to destroy enough to turn the tide of the battle. At this point the lesser numbers make it easier to kill the remaining zombies and the tempo drops off; hence the difficulty rises and falls according to a predefined difficulty curve). It would have been obvious to one of ordinary skill in the art to combine the method of Anderson with the difficulty curve of Game Pace in order to create a well paced level to provide moments of action interjected with calm (see Game Pace pg 8, 3rd par.)
Claim(s) 8 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Anderson (US 2018/0361254 A1) in view of Aghdaie et al. (US 2017/0259177 A1).
Regarding claims 8 and 18, Anderson discloses the method as discussed above. However, Anderson does not explicitly disclose wherein the determining that the difference between the APD score associated with the avatars participating in the multiuser event and the SPD score is outside of the threshold comprises at least one of: (i) predicting a time point when at least one avatar of a subset of avatars participating in the multiuser event will stop participating in the multiuser event; and the modulating the at least one subset of avatars participating in the multiuser event occurs before the predicted time point; or (ii) predicting a duration before an end of the multiuser event; and the modulating the at least one subset of avatars participating in the multiuser event occurs within the predicted duration.
Aghdaie teaches a system and method which can perform automatic granular difficulty adjustment in a video game using prediction models and wherein the determining that the difference between the APD score associated with the avatars participating in the multiuser event and the SPD score is outside of the threshold comprises at least one of: (i) predicting a time point when at least one avatar of a subset of avatars participating in the multiuser event will stop participating in the multiuser event; and the modulating the at least one subset of avatars participating in the multiuser event occurs before the predicted time point; or (ii) predicting a duration before an end of the multiuser event; and the modulating the at least one subset of avatars participating in the multiuser event occurs within the predicted duration (see par. [0068], The output data 174 can be a retention rate or churn rate associated with a prediction that a user ceases to play the video game 112. For example, in some embodiments, the retention rate may be between 0 and 100 indicating the predicted percentage of users associated with similar or the same data as included as input data 172 who would cease to play the video game 112 within a threshold time period). It would have been obvious to one of ordinary skill in the art to combine the method of Anderson with the prediction models of Aghdaie in order to utilize a mapping data repository to determine how to dynamically adjust the difficulty of the game, such as, for example, changing the values of one or more knobs to make portions of the game less difficult (see Aghdaie, par. [0029]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Johnson (US 2010/0304839 A1), Conkwright (US 2007/0066403 A1), Ntoulas et al. (US 2016/0067612 A1)
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/ALLEN CHAN/Primary Examiner, Art Unit 3715 3/17/2026