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 .
DETAILED ACTION
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 1/9/25, 4/14/25, 6/3/25 was acknowledged. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, or 365(c) is acknowledged. This application discloses and claims only subject matter disclosed in prior application no 17/472650, filed 9/12/21, and names the inventor or at least one joint inventor named in the prior application. Accordingly, this application constitutes a continuation.
Claim Objections
Claim 9 is objected to because of the following informalities: Applicant is recommended to amend the phrase "pertainto" to "pertain to".
Claim 18 is objected to because of the following informalities: Applicant is recommended to amend the phrase "-such that" to "such that", “or earlier” to “earlier”. Appropriate correction is required.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory obviousness-type double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the conflicting application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement.
Effective January 1, 1994, a registered attorney or agent of record may sign a terminal disclaimer. A terminal disclaimer signed by the assignee must fully comply with 37 CFR 3.73(b).
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 12145064. Although the claims at issue are not identical, they are not patentably distinct from each other because claims 1-20 of the present application are merely broader in scope than that of U.S. Patent No. 12145064. Therefore, U.S. Patent No. 12145064 “invention” meets the limitations of the instant application.
Instant Application
U.S. Patent No. 12145064
1. An apparatus comprising: at least one processor system configured to: subsequent to training a machine learning (ML) model on plural computer game strategies comprising statistics as to the outcomes of character action, input to the ML model a current game information; use the ML model to output an advisory to a player of a computer game generating the current game information regarding changing one or more of a computer game character, a mechanic, a location, an activity; and present the advisory on at least one computer display, wherein the statistics comprise boss kills and/or character survival time and/or highest game level attained and/or total enemies killed and/or how quickly a character died. .
1. A system comprising: at least one computer medium that is not a transitory signal and that comprises instructions executable by at least one processor to: train at least a first machine learning (ML) model on plural computer game strategies, at least some of the strategies comprising at least one computer game character executing at least one activity using at least one mechanic in at least one computer game location, the at least some of the strategies being associated with ground truth outcomes; subsequent to training, input to the ML model a current game information; use the ML model to output an advisory to a player of a computer game generating the current game information regarding changing one or more of a computer game character, a mechanic, a location, an activity; and present the advisory on at least one computer display, wherein presenting the advisory depends on a difficulty level such that a lower difficulty level results in presenting an advisory more often than an advisory is presented for a higher difficulty level.
18. An apparatus comprising: at least one processor system configured to: subsequent to training a machine learning (ML) model on plural computer game strategies, input to the ML model a current game information; use the ML model to output an advisory to a player of a computer game generating the current game information; and present the advisory on at least one computer display, wherein presenting the advisory depends on a difficulty level such that a lower difficulty level results in presenting an advisory or earlier in a game than an advisory is presented for a higher difficulty level.
19. A system comprising: at least one computer medium that is not a transitory signal and that comprises instructions executable by at least one processor to: train at least a first machine learning (ML) model on plural computer game strategies, at least some of the strategies comprising at least one computer game character executing at least one activity using at least one mechanic in at least one computer game location, the at least some of the strategies being associated with ground truth outcomes; subsequent to training, input to the ML model a current game information; use the ML model to output an advisory to a player of a computer game generating the current game information regarding changing one or more of a computer game character, a mechanic, a location, an activity; and present the advisory on at least one computer display, wherein presenting the advisory depends on a difficulty level, such that a lower difficulty level results in presenting an advisory or earlier in a game than an advisory is presented for a higher difficulty level.
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.
In the instant application, claim(s) 1-20 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Step 1:
Claim(s) 1-20 is/are drawn to at least one of the four statutory categories of invention (i.e. process, machine, manufacture, or composition).
Step 2A:
However, claim(s) 1-20 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
For instance, regarding independent claim(s) 1, 18,
Prong 1 analysis:
The limitations of “subsequent to training a machine learning (ML) model on plural computer game strategies comprising statistics as to the outcomes of character action, input to the ML model a current game information; use the ML model to output an advisory to a player of a computer game generating the current game information regarding changing one or more of a computer game character, a mechanic, a location, an activity; and present the advisory on at least one computer display, wherein the statistics comprise boss kills and/or character survival time and/or highest game level attained and/or total enemies killed and/or how quickly a character died” (claim 1), “input to the ML model a current game information; use the ML model to output an advisory to a player of a computer game generating the current game information; and present the advisory on at least one computer display, wherein presenting the advisory depends on a difficulty level such that a lower difficulty level results in presenting an advisory or earlier in a game than an advisory is presented for a higher difficulty level” (claim 18), are considered to fall within the mental processes grouping. The recited limitations, as drafted, cover performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting generic computer elements, nothing in the claim element precludes the step from practically being performed in the mind.
Furthermore, dependent claims 2-17, 19-20 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 generally linking the use of the abstract idea to a particular technological environment or field of use because they are merely incidental or token additions to the claims that do not alter or affect how the process steps are performed.
Prong 2 analysis:
The above-identified abstract idea is not integrated into a practical application under the 2019 PEG because the additional elements “at least one processor system configured to: subsequent to training a machine learning (ML) model on plural computer game strategies comprising statistics as to the outcomes of character action”, are generically recited computer elements that do not improve the functioning of a computer, or any other technology or technical field. Nor do these additional elements serve to apply the above-identified abstract idea with, or by use of, a particular machine, effect a transformation or apply or use the above-identified abstract idea in some other meaningful way beyond generally linking the use thereof to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. Furthermore, the above-identified generically recited computer elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. For at least these reasons, the abstract idea identified above is not integrated into a practical application under the 2019 PEG.
Moreover, the above-identified abstract idea is not integrated into a practical application under the 2019 PEG because the claimed method and system merely implements the above-identified abstract idea using rules (e.g., computer instructions) executed by a computer. The claimed elements are recited at a high level of generality, and amounts to mere data gathering and data transmission, which is a form of insignificant extra-solution activity. Each of the additional limitations are no more than mere instructions to apply the exception using generic computer components. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Step 2B:
As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using generic computer components. The same analysis applies here in 2B, i.e., mere instructions to apply an exception using generic computer components cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Furthermore, in view of Berkheimer, the recited additional elements are considered as conventional activity. For instance, Pardeshi et al. (2021/0397971) and Yilmazcoban et al. (2020/0324206) teaches the recited additional elements (Pardeshi, ¶¶0001, 0045-0046, 0055, 0084, 0379; Yilmazcoban, ¶¶0018-0020, 0024-0025, 0038, 0060).
In addition, with regards to the present claims, the courts have recognized the computer functions as well‐understood, routine, and conventional activities when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
For instance, regarding claims 1-20, each claim describes physical or software elements that provide a generic environment in which to carry out the abstract idea, which is similar to the conventional activity or as insignificant extra-solution activity of selecting information, based on types of information, for collection, analysis and display in EPG, gathering, receiving and transmitting data in Symantec, TLI, OIP Techs., buySAFE.
Therefore, claim(s) 1-20 is/are therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
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, 3-6 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Beltran et al. (10576380).
Re Claim 1,
Beltran discloses an apparatus comprising: at least one processor system configured to:
subsequent to training a machine learning (ML) model on plural computer game strategies comprising statistics as to the outcomes of character action, input to the ML model a current game information (Fig 1A, 3A, col 7, ln 25-46, col 8, ln 13-31, col 18, ln 25-65; the training data includes controller input used to direct corresponding game plays, game states of the instances of the gaming application occurring during the game plays, response metrics, success criteria, success metrics, additional analysis performed on the game plays, etc. further, the analyzer is configured to analyze the output from the trained AI model for a given input and provide a response);
use the ML model to output an advisory to a player of a computer game generating the current game information regarding changing one or more of a computer game character, a mechanic, a location, an activity (Fig 3A, col 8, ln 13-31, col 18, ln 25-65, col 21, ln 48-60, col 22, ln 12-45, col 23, ln 28-49; the trained AI model may provide a recommendation to the player based on the current game information); and
present the advisory on at least one computer display, wherein the statistics comprise boss kills and/or character survival time and/or highest game level attained and/or total enemies killed and/or how quickly a character died (col 8, ln 13-31, col 18, ln 25-65, col 21, ln 48-60, col 22, ln 12-45, col 23, ln 28-49, col 27, ln 34-51; the recommendation is provided and displayed to the player, further, the training data includes historical and current game play information).
Re Claim 3,
Beltran discloses the advisory regards changing a mechanic (col 8, ln 13-31, col 18, ln 25-65, col 21, ln 48-60, col 22, ln 12-45, col 23, ln 28-49, col 27, ln 34-51).
Re Claim 4,
Beltran discloses the advisory regards changing a location (col 8, ln 13-31, col 18, ln 25-65, col 21, ln 48-60, col 22, ln 12-45, col 23, ln 28-49, col 27, ln 34-51).
Re Claim 5,
Beltran discloses the advisory regards changing an activity (col 8, ln 13-31, col 18, ln 25-65, col 21, ln 48-60, col 22, ln 12-45, col 23, ln 28-49, col 27, ln 34-51).
Re Claim 6,
Beltran discloses arranging game play historical data in a database according to object types employed in respective computer games, the object types comprising computer game characters, computer game activities, computer game mechanics, computer game locations (col 8, ln 13-31, col 18, ln 25-65, col 21, ln 48-60, col 22, ln 12-45, col 23, ln 28-49, col 27, ln 34-51).
Re Claim 9,
Beltran discloses the statistics pertain to outcomes of characters operating mechanics in various zones or locations to execute certain activities (col 8, ln 13-31, col 18, ln 25-65, col 21, ln 48-60, col 22, ln 12-45, col 23, ln 28-49, col 27, ln 34-51).
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.
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.
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Beltran et al. (10576380) in view of Kumar et al. (2019/0388785).
Re Claim 2,
Beltran discloses all limitations as set forth above but does not explicitly disclose presenting the advisory depends on a difficulty level such that a lower difficulty level results in presenting an advisory more often than an advisory is presented for a higher difficulty level. However, Kumar teaches presenting the advisory depends on a difficulty level such that a lower difficulty level results in presenting an advisory more often than an advisory is presented for a higher difficulty level (¶¶0065-0068; the game assistance may be tailored based on a particular difficulty level, for instance, the system may decline to provide any assistance if the confidence level is above a threshold). Kumar further teaches such a configuration can lessen a user’s frustration to complete a certain objective with the video game (¶0002). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to utilize the teaching of Kumar into the game advice of Beltran in order to lessen a user’s frustration to complete a certain objective with the video game.
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Beltran et al. (10576380) in view of Gurumurthy et al. (2020/0269136).
Re Claim 7,
Beltran discloses all limitations as set forth above but does not explicitly disclose the mechanic includes a weapon. However, Gurumurthy teaches the mechanic includes a weapon (¶0021). Gurumurthy further teaches such a configuration can improve a player’s skill level or game strategies for specific games (¶0001). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to utilize the teaching of Gurumurthy into the game suggestion of Yilmazcoban in order to improve a player’s skill level or game strategies for specific games.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Beltran et al. (10576380) in view of Benedetto et al. (2020/0122043).
Re Claim 8,
Beltran discloses all limitations as set forth above but does not explicitly disclose the mechanic includes a vehicle. However, Benedetto teaches the mechanic includes a vehicle (¶0048). Benedetto further teaches such a configuration allows the player to try out better approaches and make progress in the game (¶0006). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to utilize the teaching of Benedetto into the game suggestion of Yilmazcoban in order to allow the player to try out better approaches and make progress in the game.
Claim(s) 10-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Beltran et al. (10576380) in view of Vonderhaar et al. (2017/0021274).
Re Claim 10,
Beltran discloses all limitations as set forth above but does not explicitly disclose boss kills, survival time, highest game level attained, total enemies killed, how quickly the character died, missed shots. However, Vonderhaar teaches a video game that collects various gameplay statistics including number of kills, accuracy, kill-to-death ratio, win-loss ratio, kills per minute, score, or other statistics, number of shots fired, number of games played, time played, weapon progress, individual player performance rating, global player performance rating, and/or other information related to the gameplay (¶¶0026, 0143). Vonderhaar further teaches such a configuration improves player experience by creating and sharing gameplay information with the player (¶¶0007, 0010). In addition, it would have been an obvious matter of design choice for collecting a particular type of gameplay data, since Applicant has not disclosed that collecting a particular type of gameplay data solves any stated problem. As such, it would have been obvious to one of ordinary skill in the art to collect a particular type of gameplay data to achieve the most desired data collection since discovering the optimum data collection involves only routine skill in the art.
Claim(s) 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Beltran et al. (10576380) in view of Mizuki et al. (2017/0302611).
Re Claim 16,
Beltran discloses all limitations as set forth above but does not explicitly disclose tactilely. However, Mizuki teaches display recommendation on a touch screen, i.e., tactilely (¶0070). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to utilize the touch screen taught by Mizuki into the game suggestion of Beltran in order to provide a convenient way for the player to interact with the game.
Claim(s) 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Beltran et al. (10576380) in view of Hamaguchi et al. (2021/0268377).
Re Claim 17,
Beltran discloses all limitations as set forth above but does not explicitly disclose presenting the difficulty level is set by the player. However, Hamaguchi teaches the player setting a difficulty level (¶0126). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to utilize the teaching of allowing a player to select game difficulty level taught by Hamaguchi into the game of Beltran in order to enhance the player’s game experience.
Claim(s) 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Beltran et al. (10576380) in view of Aghdaie et al. (2019/0358545).
Re Claim 18,
Beltran discloses all limitations as set forth above including subsequent to training a machine learning (ML) model on plural computer game strategies, input to the ML model a current game information; use the ML model to output an advisory to a player of a computer game generating the current game information but is silent on presenting the advisory depends on a difficulty level such that a lower difficulty level results in presenting an advisory earlier in a game than an advisory is presented for a higher difficulty level. Aghdaie teaches presenting the advisory depends on a difficulty level such that a lower difficulty level results in presenting an advisory or earlier in a game than an advisory is presented for a higher difficulty level (¶¶0022, 0054, 0056; the recommendations presented to the user can be tailored to the user's level of skill, i.e., a level skill level is considered as a lower difficulty level. For example, the user can be presented with tutorial information corresponding to moves that the user has not yet mastered in gameplay, while information for moves that the user has already been able to perform successfully are not presented, that is, the advice is presented to the beginner level user earlier in the game). Aghdaie further teaches such a configuration accommodates both beginners and advanced players (¶0002). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to utilize the teaching of Aghdaie into the game advice of Beltran in order to accommodate both beginners and advanced players.
Claim(s) 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Beltran et al. (10576380) in view of Aghdaie et al. (2019/0358545), further in view of Hamaguchi et al. (2021/0268377).
Re Claim 19,
Beltran as modified by Aghdaie discloses all limitations as set forth above but does not explicitly disclose the difficulty level is set by the player. However, Hamaguchi teaches the player setting a difficulty level (¶0126). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to utilize the teaching of allowing a player to select game difficulty level taught by Hamaguchi into the game of Beltran in order to enhance the player’s game experience.
Claim(s) 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Beltran et al. (10576380) in view of Aghdaie et al. (2019/0358545), further in view of Kumar et al. (2019/0388785).
Re Claim 20,
Claim is substantially similar to claim 2. See claim 2 for rejection and motivation.
Conclusion
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/JASON T YEN/Primary Examiner, Art Unit 3715
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