WO2022267276A1 - 一种人机对弈方法、装置、设备、存储介质及程序产品 - Google Patents
一种人机对弈方法、装置、设备、存储介质及程序产品 Download PDFInfo
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
- A63F13/60—Generating or modifying game content before or while executing the game program, e.g. authoring tools specially adapted for game development or game-integrated level editor
- A63F13/67—Generating or modifying game content before or while executing the game program, e.g. authoring tools specially adapted for game development or game-integrated level editor adaptively or by learning from player actions, e.g. skill level adjustment or by storing successful combat sequences for re-use
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F3/00—Board games; Raffle games
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
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- A63F13/79—Game security or game management aspects involving player-related data, e.g. identities, accounts, preferences or play histories
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F3/00—Board games; Raffle games
- A63F3/02—Chess; Similar board games
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F2300/00—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game
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- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
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- A63F2300/60—Methods for processing data by generating or executing the game program
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Definitions
- Embodiments of the present disclosure relate to the field of data processing, and relate to a method, device, equipment, storage medium, and program product for man-machine games.
- AI artificial intelligence
- the use of man-machine games is becoming more and more extensive.
- some AI chess power models of different levels are usually preset, and users can manually set them before each game according to their own judgment and selection. This method depends on the user himself.
- the subjective judgment ability of the game usually leads to the wrong level selection due to reasons such as difficulty in judging its own ability. It is difficult for the user to experience the feeling of meeting the opponent quickly during the game, which affects the user's interest in the game.
- Embodiments of the present disclosure provide a method, device, equipment, storage medium, and program product for a human-computer game.
- a method for man-machine game including:
- the second move strategy corresponding to the second party is generated based on the current move position corresponding to the move event and the historical move record; the second move strategy Including a plurality of second candidate positions and a second party winning rate corresponding to each second candidate position;
- the chess power quantization value is used to characterize the chess power level of the first party
- a target position is determined in the plurality of second candidate positions; the winning ratio of the second party corresponding to the target position matches the chess quantization value.
- the determining the chess strength value of the first party based on the historical record of moves and the current position of moves includes:
- the determining the target drop position in the plurality of second candidate positions includes:
- the preset first mapping table obtain the target ranking position corresponding to the chess score of the first party; the first mapping table includes the mapping relationship between the chess score and the ranking position;
- the second candidate position corresponding to the target sorting position is determined as the target drop position.
- the determining the target drop position in the plurality of second candidate positions includes:
- a second candidate position located in the target winning percentage interval is determined as the target betting position.
- the real-time chess score of the first party in the current round is determined, and based on the real-time chess score in the second move strategy, it is obtained that the first chess player is in the same position as the first chess player.
- There is a target position where there is a mapping relationship between the real-time winning rate of the player, and the effect of "meeting opponents" can be achieved between the first player and the second player in the current game process.
- the method in the response to the move event of the first party in the current round, based on the first current move corresponding to the move event and the historical move record, the second party corresponding to the first move is generated.
- the method also includes: based on the historical move record, predicting the first move strategy corresponding to the first party; the first move strategy includes a plurality of first candidate positions and each of the The winning rate of the first party corresponding to the first candidate position;
- the determining the chess strength value of the first party based on the historical record and the current position of the position includes: determining the current position based on the winning rate of the first party corresponding to each of the first positions to be selected.
- the winning percentage of the first party corresponding to the position; the winning percentage of the first party corresponding to the current falling position is determined as the chess power quantization value.
- the determining the target drop position in the plurality of second candidate positions includes:
- the target betting position is determined in the plurality of second candidate positions; there is a mapping relationship between the winning rate of the second party of the target betting position and the winning rate of the first party.
- the first party's move strategy in the current round is predicted after the second party's move, it is obtained that the first party's corresponding positions include a plurality of first candidate positions and each of the first candidate positions The first move strategy of the first party's winning rate corresponding to the position. Furthermore, in the current round, the chess strength value of the first party can be quickly determined after the first party makes a move, thereby increasing the speed of the second party's move in the current round. At the same time, because the first party's real-time winning rate in the current round is determined based on the current position of the first party in the current round, and based on the real-time winning rate, the real-time winning rate of the first party is obtained in the second move strategy. The target position can realize the effect of "meeting opponents" between the first party and the second party in the current game process.
- the historical play record includes the play time; the method also includes:
- the first party's average move time is used to characterize the first party's move speed after the second party's move;
- the third move strategy includes multiple A third position to be selected; the third position to be selected is related to the chess power value of the first party in the historical round;
- a fourth move strategy corresponding to the second party For each of the third candidate positions, based on the third candidate position and the historical record, a fourth move strategy corresponding to the second party is generated; the fourth move strategy includes a plurality of fourth moves The candidate position and the second-party winning rate corresponding to each of the fourth candidate positions;
- the second move strategy is obtained from the fourth move strategy corresponding to each of the third candidate positions based on the current move position corresponding to the move event.
- the average move time of the first party is determined, and when the average move time satisfies the preset condition, after the second party completes the move in the last round, use the first
- the thinking time of one party not only predicts the third move strategy of the first party in the current round, but also generates multiple fourth move strategies of the second party based on the third move strategy.
- the second move strategy corresponding to the first party's current move position can be directly determined from a plurality of fourth move strategies, which improves the second party's current round for the second move strategy.
- the response speed of one party's move event in the current round improves the experience of real users.
- the obtaining the average duration of the first party's moves based on the historical record of moves includes:
- At least one first time interval is determined; the first time interval is the betting time of the second party The time interval between the betting time of the first party and the betting time of the adjacent first party's betting;
- An average move duration for the first party is generated based on the at least one first time interval.
- the method also includes:
- Prompt information is generated based on the chess power quantization value of the first party in the historical round and the chess power quantization value of the first party in the current round; the prompt information is used to represent the first party in different rounds Changes in chess strength.
- the prompt information for representing the change of the first party's chess power in different rounds is generated.
- the real user can receive real-time feedback corresponding to the current move event.
- the user can perceive the move corresponding to the current round is relatively better through the first prompt information;
- the quantitative value is reduced, the user can perceive that the move corresponding to the current round is relatively poor through the second prompt information; thus, it can not only improve the timeliness of feedback to the user in the man-machine game method, but also enable the user to perceive
- the real-time effect of each step improves the learning efficiency of real users.
- a man-machine game device including:
- the recording part is configured to record the position of the first party and the second party during the game, and obtain the historical record of the position;
- the generating part is configured to generate a second move strategy corresponding to the second party based on the current move position corresponding to the move event and the historical move record in response to the move event of the first party in the current round;
- the second placement strategy includes a plurality of second candidate positions and a second winning rate corresponding to each of the second candidate positions;
- the determination part is configured to determine the chess power quantization value of the first party in the current round based on the historical move record and the current move position; the chess power quantization value is used to characterize the chess power of the first party Level;
- the move part is configured to determine a target move position among the plurality of second candidate positions; the winning ratio of the second party corresponding to the target move position matches the chess power quantization value.
- a human-computer game device including: a memory and a processor, the memory stores a computer program that can run on the processor, and the processor implements the above method when executing the computer program A step of.
- a computer storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in the above method.
- a computer program product including computer readable codes, and when the computer readable codes are run in an electronic device, a processor in the electronic device executes the steps for implementing the above method.
- the chess power value of the first party in the current round is obtained, and based on the chess power of the first party in the current round Quantified value, select the second candidate position whose winning rate of the second party matches the chess strength value as the target position of the second party, which can realize the dynamic Adjusting the virtual user's move strategy to dynamically match the virtual user's chess skill level with the real user's chess skill level can make the real user feel the feeling of "meeting the opponent" during the game, and enhance the user's interest in the game.
- FIG. 1 is a schematic flow diagram of a man-machine game method provided by an embodiment of the present disclosure
- FIG. 2 is a schematic flow diagram of a man-machine game method provided by an embodiment of the present disclosure
- FIG. 3 is a schematic flowchart of a man-machine game method provided by an embodiment of the present disclosure
- FIG. 4 is a schematic flowchart of a man-machine game method provided by an embodiment of the present disclosure
- FIG. 5 is a schematic flowchart of a method for man-machine game provided by an embodiment of the present disclosure
- FIG. 6 is a schematic flow diagram of a human-computer game method provided by an embodiment of the present disclosure.
- FIG. 7 is a schematic flow diagram of a human-computer game method provided by an embodiment of the present disclosure.
- FIG. 8 is a schematic diagram of the composition and structure of a human-machine game device provided by an embodiment of the present disclosure.
- FIG. 9 is a schematic diagram of a hardware entity of a human-computer game device provided by an embodiment of the present disclosure.
- Fig. 1 is a schematic flowchart of a method for man-machine game provided by an embodiment of the present disclosure. As shown in Fig. 1, the method includes:
- the man-machine game method provided by the embodiments of the present disclosure can be used for various chess games, which can include at least one of Go, Chinese Chess, International Chess, Military Flag, Backgammon, Checkers, and Flying Chess. A sort of.
- the first party is a real user party
- the second party is a machine party, that is, a virtual user party.
- at least one first party and at least one second party are included, and the numbers of the first party and the second party can be changed based on different types of chess.
- first party and one second party can be included in a game, that is, one real user party and one virtual user party are allowed to participate in the game;
- chess games such as military flag, checkers and flying chess
- only one first party and one second party can be included, or one first party and a plurality of second parties can be included, and a plurality of second parties can also be included.
- the first party and multiple second parties may also include multiple first parties and one second party. The embodiment of the present disclosure does not limit this.
- the historical move records may include all move information of the first party and the second party.
- Each bet information may include at least one of the following: bet user, bet time, bet location, etc.
- the move information also includes the move type.
- the corresponding move information can only include the player who made the move and the time of the move, and information such as the position of the move can be set is null. in. Go allows one party to choose not to make a move, and let the other party continue to make a move. This is "passing a hand (pass)".
- the above-mentioned current round is a round that includes the first party making moves, and then the second party making moves.
- a move event of the first party in the current round is generated, and at the same time, the move event can carry move information.
- the second party needs to make a move.
- at least the current position of the move should be considered to improve the first move.
- the pertinence of the two parties' moves in the current round at the same time, in addition to considering the current position of the move, it is also necessary to consider the historical record of moves to improve the pertinence of the second party's moves in the overall game process.
- the second party in the process of generating the second party's corresponding move strategy based on the current move position and historical move records corresponding to the move event, can be generated based on all move information in the historical move records and the current move position.
- the move strategy corresponding to the first party; the move strategy corresponding to the second party can also be generated based on part of the move information in the historical move record and the current move position.
- the second move strategy corresponding to the second party may include a plurality of second candidate positions and a winning rate of the second party corresponding to each of the second candidate positions.
- the plurality of second candidate positions generated may include the position information of all available positions of the second party in the current round. For example, for a game of Go, all empty positions on the chessboard may be the positions of the second party. Therefore, the plurality of second candidate positions may be all the above-mentioned empty betting points; the generated plurality of second candidate positions may include the betting points whose winning rate of the second party exceeds the minimum winning rate threshold.
- the chess power quantization value of the first party in the current round is determined based on the current position, the chess power quantization value can be used to represent the corresponding chess power of the first party in the current round Level. That is to say, in different rounds, step S103 can determine the chess power level of the first party in different rounds based on different historical records of moves and different current positions of moves.
- the chess power level of the opposing player can be determined through the preset chess power evaluation model.
- a plurality of move information arranged in time sequence can be input into the The chess strength evaluation model obtains the chess strength level of each player in the latest round in the multiple move information.
- the obtained multiple move information includes A1, B1, A2, B2, . . . , AN, BN, AN+1.
- the chess power value of the A side in the N+1 round and the chess power value of the B side in the N round can be obtained.
- the second candidate position directly according to the first party's chess power value in the current round.
- the second candidate position that has a mapping relationship between the winning percentage of the second party and the chess power value is used as the target position.
- the betting event of the second party in the current round may be completed based on the target betting position.
- the current round of the man-machine game process ends, and the next round of man-machine game process starts.
- the historical record of the next round includes the positions of the first party and the second party in the current round.
- the chess power value of the first party in the current round is obtained, and based on the chess power of the first party in the current round Quantified value, select the second candidate position whose winning rate of the second party matches the chess strength value as the target position of the second party, which can realize the dynamic Adjusting the virtual user's move strategy to dynamically match the virtual user's chess skill level with the real user's chess skill level can make the real user feel the feeling of "meeting the opponent" during the game, and enhance the user's interest in the game.
- Fig. 2 is an optional flowchart of the human-computer game method provided by the embodiment of the present disclosure. Based on Fig. 1, S103 in Fig. 1 can be updated to S201 to S202, and S104 can be updated to step S203, combining The steps shown in Figure 2 are described.
- step S2031 can be used to realize the above-mentioned determination of the target drop position among the plurality of second candidate positions:
- the first mapping table is used to obtain the target ranking position corresponding to the first party's chess score; the first mapping table includes the mapping relationship between the chess score and the ranking position; determine the second candidate position corresponding to the target ranking position For the target drop position.
- the first mapping table may include a plurality of chess skill scoring intervals and a sorting position corresponding to each chess skill scoring interval.
- the first mapping table may include chess power scoring interval F1: [0, 20), chess power scoring interval F2: [20, 40), chess power scoring interval F3: [40, 60), chess power scoring interval F4: [60, 80), chess power score interval F5: [80, 100].
- the sorting position corresponding to the chess power scoring interval F1 is the 5th
- the sorting position corresponding to the chess power scoring interval F2 is the 4th
- the sorting position corresponding to the chess power scoring interval F3 is the 3rd
- the sorting position corresponding to the chess power scoring interval F4 is The ranking position corresponding to the second place and the chess power score interval F5 is the first place.
- the obtained second placement strategy includes: the second party’s winning rate corresponding to the second candidate position A1 is 50%, the second party’s winning rate corresponding to the second candidate position A2 is 80%, and the second candidate position A3 corresponds to The winning rate of the second party in the second position A4 is 70%, the winning rate of the second party corresponding to the second candidate position A4 is 60%, the winning rate of the second party corresponding to the second candidate position A5 is 90%, and the winning rate of the second party corresponding to the second candidate position A6 is 90%.
- the winning rate of the two sides is 95%, and there are 6 second candidate positions in total.
- the corresponding sort position is 6
- the second candidate position A2 corresponds to The sorting position corresponding to the second candidate position A3 is 3, the sorting position corresponding to the second candidate position A3 is 4, the corresponding sorting position of the second candidate position A4 is 5, the corresponding sorting position of the second candidate position A5 is 2, and the second candidate position A5
- the sorting position corresponding to A6 is 1.
- the corresponding target sorting position is the second, that is, the second candidate position A5 whose sorting position is 2 is taken as the target drop position.
- step S2032 can be used to realize the above-mentioned determination of the target drop position among the plurality of second candidate positions:
- the preset second mapping table obtain the target winning percentage interval corresponding to the chess power score of the first party; based on the target winning percentage interval, determine the second candidate position located in the target winning percentage interval as the selected position Describe the target drop position.
- the second mapping table may include a plurality of chess power scoring intervals and a winning percentage interval corresponding to each chess power scoring interval.
- the first mapping table may include the chess power score interval F1: [0, 20) corresponding to the winning percentage interval is also [0, 20), chess power scoring interval F2: [20, 40) corresponding winning percentage interval is also [20, 40) , Chess power scoring interval F3: [40, 60) corresponds to the winning percentage interval is also [40, 60), chess power scoring interval F4: [60, 80) corresponding winning percentage interval is also [40, 60), chess power scoring interval F5: [80 , 100] corresponds to the winning rate interval is also [40, 60).
- the obtained second placement strategy includes: the second party’s winning rate corresponding to the second candidate position A1 is 50%, the second party’s winning rate corresponding to the second candidate position A2 is 80%, and the second candidate position A3 corresponds to The winning rate of the second party corresponding to the second candidate position A4 is 70%, the winning rate of the second party corresponding to the second candidate position A4 is 60%, the winning rate of the second party corresponding to the second candidate position A5 is 90%, and the winning rate of the second party corresponding to the second candidate position A6 is 90%.
- the winning rate of the two sides is 95%, and there are 6 second candidate positions in total.
- the chess score of the first party is 65, it can be determined that the corresponding target winning percentage interval is also [40, 60), and then the second candidate position A1 is used as the target position. .
- the real-time chess score of the first party in the current round is determined, and based on the real-time chess score in the second move strategy, it is obtained that the first chess player is in the same position as the first chess player.
- There is a target position where there is a mapping relationship between the real-time winning rate of the player, and the effect of "meeting opponents" can be achieved between the first player and the second player in the current game process.
- FIG. 3 is an optional flowchart of the human-computer game method provided by the embodiment of the present disclosure. Based on FIG. 1, the method in FIG. 1 also includes S301, S103 can be updated to S302, and S104 can be updated to S303. It will be described in conjunction with the steps shown in FIG. 3 .
- the first move strategy includes a plurality of first candidate positions and a first position corresponding to each first candidate position Party win rate.
- the first party's move in the current round may be based on the historical move record. Predict the position of the round. That is, in response to the move event of the second party in the last round, based on the historical move record, predict the first move strategy corresponding to the first party.
- the method for generating the first move strategy corresponding to the first party may be the same as in S102, based on the current move position and the historical move record, generating the second move corresponding to the second party.
- the approach to the strategy is the same or different.
- the winning percentage of the first party corresponding to each candidate position corresponding to the first party can be obtained.
- the user's current betting position in the current round has been obtained. Search for a corresponding target candidate position in each candidate position obtained in S301 based on the current move position, and use the winning rate of the first party corresponding to the target candidate position as the chess strength value.
- all positions to be selected and the corresponding winning percentages of the first party have not yet been output.
- a candidate position, and the winning rate of the first party corresponding to each candidate position based on the current position of the current round of the drop event, search for a matching target candidate position among the obtained at least one candidate position, if a match can be found the target candidate position, stop the prediction process of S301, and use the winning rate of the first party corresponding to the obtained target candidate position as the above-mentioned chess power quantization value; if no matching target candidate position is found, then continue to execute the prediction process of S301, Until the target candidate position matching the current drop position is obtained.
- the second party's winning rate corresponding to each candidate position after obtaining multiple candidate positions corresponding to the second party, and the second party's winning rate corresponding to each candidate position, it can be based on the above-mentioned chess quantization value, that is, the first party's winning rate corresponding to the current position. , determining the target drop position in which the winning rate of the second party and the winning rate of the first party have a mapping relationship among the plurality of second candidate positions.
- At least one of the following implementation methods can be used to realize the above-mentioned target position where the second party's winning rate and the first party's winning rate have a mapping relationship in the plurality of second candidate positions:
- the preset mapping function relationship can be determined by the basic first-party winning rate and offset parameters, wherein the basic first-party winning rate can be set by the user, and the default value is 50%. In the case of the value, it indicates that the difficulty of the first party is higher for the user, and when the basic first party win rate is less than the default value, it indicates that the difficulty of the first party is lower for the user; the offset parameter is used for the second party
- the difference between one party's winning rate and the basic first party's winning rate is scaled to determine the converted first party's winning rate, where the mapping function relationship can be expressed as the following formula:
- P after conversion represents the converted first-party winning percentage
- P before conversion represents the first-party winning percentage corresponding to the current betting position
- P basis represents the basic first-party winning percentage
- k is an offset parameter.
- the first party's move strategy in the current round is predicted after the second party's move, it is obtained that the first party's corresponding positions include a plurality of first candidate positions and each of the first candidate positions The first move strategy of the first party's winning rate corresponding to the position. Furthermore, in the current round, the chess strength value of the first party can be quickly determined after the first party makes a move, thereby increasing the speed of the second party's move in the current round. At the same time, because the first party's real-time winning rate in the current round is determined based on the current position of the first party in the current round, and based on the real-time winning rate, the real-time winning rate of the first party is obtained in the second move strategy. The target position can realize the effect of "meeting opponents" between the first party and the second party in the current game process.
- Fig. 4 is an optional flowchart of the human-computer game method provided by the embodiment of the present disclosure. Based on any of the above embodiments, taking Fig. 1 as an example, S102 in Fig. 1 can be updated to S401 to S404 , which will be described in conjunction with the steps shown in FIG. 4 .
- steps S4011 to S4012 can be used to obtain the average duration of the first party's moves based on the historical record of moves:
- S4011 Determine at least one first time interval based on at least one move time of the first party and at least one move time of the second party in the historical move records; the first time interval is the second The time interval between the move time of the square's move and the move time of the adjacent first party's move.
- the average move duration of the first party satisfies a preset condition, based on the historical move records, predict the third move strategy of the first party in the current round; the third move strategy A plurality of third candidate positions are included; the third candidate positions are related to chess power values of the first party in historical rounds.
- the second party's average move time is used to characterize the second party's move speed after the first party's move; In the case where the average move time of the first party is greater than or equal to the average move time of the second party, it is determined that the average move time of the first party satisfies the preset condition; If the average move time is less than the average move time of the second party, it is determined that the average move time of the first party does not satisfy the preset condition.
- the position of the first party in the current round before receiving the current position of the first party in the current round, the position of the first party in the current round can be predicted based on the historical record, and the position of the first party in the current round can be obtained.
- the third play strategy of the round includes a plurality of third candidate positions and the winning rate of the first party corresponding to each of the third candidate positions, based on the chess strength of each historical round of the first party in the historical move records
- Quantitative values may determine at least one third candidate position relative to the historical level of the first party. It should be noted that, in the third move strategy, all third candidate positions that can be placed may be included, or only a part of the third candidate positions related to the historical level of the first party may be included.
- the fourth move strategy includes a plurality of The fourth candidate position and the winning rate of the second party corresponding to each fourth candidate position.
- the corresponding value of the second party corresponding to each third candidate position is obtained.
- Fourth betting strategy includes a plurality of fourth candidate positions and the winning ratio of the second party corresponding to each of the fourth candidate positions.
- the average move time of the first party is determined, and when the average move time satisfies the preset condition, after the second party completes the move in the last round, use the first
- the thinking time of one party not only predicts the third move strategy of the first party in the current round, but also generates multiple fourth move strategies of the second party based on the third move strategy.
- the second move strategy corresponding to the first party's current move position can be directly determined from a plurality of fourth move strategies, which improves the second party's current round for the second move strategy.
- the response speed of one party's move event in the current round improves the experience of real users.
- FIG. 5 is an optional flowchart of the human-computer game method provided by the embodiment of the present disclosure. Based on any of the above-mentioned embodiments, taking FIG. 1 as an example, the method in FIG. 1 may also include S501 to S502 , which will be described in conjunction with the steps shown in FIG. 5 .
- the historical round may only include the previous round, and the previous round is a historical round adjacent to the current round.
- the chess power value of the first party in the previous round is first obtained, combined with The previously obtained chess power value of the first party in the current round can generate corresponding prompt information, and the prompt information is used to represent the change of the chess power of the first party in the current round relative to the previous round.
- first prompt information may be generated, and the first prompt information may be used to indicate that the chess strength of the first party has improved.
- the first prompt information may be prompt information such as "good chess", “good chess”, or "really good”, which represents the improvement of the real user's chess ability.
- second prompt information may be generated, and the second prompt information may be used to indicate that the chess power of the first party has decreased.
- the first prompt information may be prompt information such as "bad chess", “mistake” or "why play here", which represents the decline of the real user's chess ability.
- the historical round may only include a plurality of historical rounds before the current round.
- S501 first obtain the first party's chess power value in each historical round, and combine the previously obtained first party's chess value in the current round.
- the chess power value of the round generates corresponding prompt information according to the number of rounds, and the prompt information is used to represent the change curve corresponding to the change of the chess power value of the first party with the number of rounds.
- the prompt information for representing the change of the first party's chess power in different rounds is generated.
- the real user can receive real-time feedback corresponding to the current move event.
- the user can perceive the move corresponding to the current round is relatively better through the first prompt information;
- the quantitative value is reduced, the user can perceive that the move corresponding to the current round is relatively poor through the second prompt information; thus, it can not only improve the timeliness of feedback to the user in the man-machine game method, but also enable the user to perceive
- the real-time effect of each step improves the learning efficiency of real users.
- AI chess power models of different levels are usually preset, and users can manually set them before each game according to their own judgment and selection. This method depends on the user himself. Subjective judgment ability, usually due to their own ability is difficult to judge, leading to wrong choices. Therefore, in the process of playing the game, either the setting is too simple, and the user has no sense of accomplishment in the game; or the setting is too difficult, which makes the user lose confidence; The solution usually requires the user to spend a long time playing multiple games in order to obtain a model that is more in line with the user's chess ability. It is difficult for users to experience the feeling of meeting opponents quickly, thereby affecting users' interest in playing games.
- the embodiment of the present disclosure provides two human-computer game methods in the implementation process, for which reference may be made to the schematic flowcharts provided in FIG. 6 and FIG. 7 .
- FIG. 6 is a schematic flow chart of an optional human-computer game method provided by an embodiment of the present disclosure, which will be described in conjunction with the steps shown in FIG. 6 .
- the historical move record includes all move positions of the user and all move positions of the AI in the process of the human-computer game.
- the chess power quantization value is used to represent the user's chess power level.
- the multiple different betting positions to be selected are sorted in descending order of winning percentage.
- a plurality of preset threshold conditions are obtained, and each threshold condition has a mapping relationship with the ranking of the winning rate. For example, there are three threshold conditions, wherein the first threshold condition has a mapping relationship with the first winning rate, the second threshold condition has a mapping relationship with the second winning rate, and the third threshold condition has a mapping relationship with the third winning rate.
- determine the target threshold condition that the user's chess power quantization value satisfies among the plurality of threshold conditions and determine the candidate move position corresponding to the target winning rate that has a mapping relationship with the target threshold condition as the target move position.
- steps S601 to S602 it is possible to dynamically identify the user's chess playing level during the game, and dynamically switch the AI chess playing strategy engine to a level that matches the user's chess playing level; and, by The above step S603 further refines the strategy in the chess-playing process, dynamically adjusts the winning strategy of the AI chess-playing engine during the game, and can switch the AI chess-playing strategy model to a level that matches the user's chess strength, further matching the user's game The playing situation in the process, so as to better match the user's chess playing level.
- the AI strategy model is used to simulate the user's move, to judge the winning rate of the user's different move positions, and according to the user's actual move position, the AI side is selected to move at the position corresponding to the winning rate, so as to achieve During the game, the winning rate of the two sides is relatively consistent, so as to achieve the self-adaptation of AI to the user's chess power.
- FIG. 7 is a schematic flow chart of an optional human-computer game method provided by an embodiment of the present disclosure, which will be described in conjunction with the steps shown in FIG. 7 .
- the historical move record includes all move positions of the user and all move positions of the AI in the process of the human-computer game.
- FIG. 8 is a schematic diagram of the composition and structure of a man-machine game device provided by an embodiment of the present disclosure. As shown in FIG. 8, the man-machine game device 800 includes:
- the recording part 801 is configured to record the position of the first party and the second party during the game, and obtain the historical record of the position;
- the generating part 802 is configured to generate a second move strategy corresponding to the second party based on the current move position corresponding to the move event and the historical move record in response to the move event of the first party in the current round ;
- the second placement strategy includes a plurality of second candidate positions and the winning rate of the second party corresponding to each of the second candidate positions;
- the determining part 803 is configured to determine the chess power quantization value of the first party in the current round based on the historical move record and the current move position; the chess power quantization value is used to represent the first party's Chess level;
- the move part 804 is configured to determine a target move position in the plurality of second candidate positions; the winning rate of the second party corresponding to the target move position matches the chess power quantization value.
- the determining part 803 is further configured to:
- the drop part 804 is further configured as:
- the preset first mapping table obtain the target ranking position corresponding to the chess score of the first party; the first mapping table includes the mapping relationship between the chess score and the ranking position;
- the second candidate position corresponding to the target sorting position is determined as the target drop position.
- the drop part 804 is further configured as:
- a second candidate position located in the target winning percentage interval is determined as the target betting position.
- the second party corresponding to the first move is generated.
- the generating part 802 is also configured to: predict the first move strategy corresponding to the first party based on the historical move record; the first move strategy includes a plurality of first candidate positions The winning rate of the first party corresponding to each of the first candidate positions;
- the determining part 803 is further configured to: determine the winning rate of the first party corresponding to the current position based on the winning rate of the first party corresponding to each of the first positions to be selected; One side's winning rate is determined as the chess power quantization value.
- the drop part 804 is further configured as:
- the target betting position is determined in the plurality of second candidate positions; there is a mapping relationship between the winning rate of the second party of the target betting position and the winning rate of the first party.
- the generating part 802 is further configured to:
- the first party's average move time is used to characterize the first party's move speed after the second party's move;
- the third move strategy includes multiple A third position to be selected; the third position to be selected is related to the chess power value of the first party in the historical round;
- a fourth move strategy corresponding to the second party For each of the third candidate positions, based on the third candidate position and the historical record, a fourth move strategy corresponding to the second party is generated; the fourth move strategy includes a plurality of fourth moves The candidate position and the second-party winning rate corresponding to each of the fourth candidate positions;
- the second move strategy is obtained from the fourth move strategy corresponding to each of the third candidate positions based on the current move position corresponding to the move event.
- the generating part 802 is further configured to:
- At least one first time interval is determined; the first time interval is the betting time of the second party The time interval between the betting time of the first party and the betting time of the adjacent first party's betting;
- An average move duration for the first party is generated based on the at least one first time interval.
- the generating part 802 is further configured to:
- Prompt information is generated based on the chess power quantization value of the first party in the historical round and the chess power quantization value of the first party in the current round; the prompt information is used to represent the first party in different rounds Changes in chess strength.
- the above-mentioned man-machine game method is implemented in the form of software functions and sold or used as an independent product, it can also be stored in a computer-readable storage medium.
- the essence of the technical solutions of the embodiments of the present disclosure or the part that contributes to the related technologies can be embodied in the form of software products, the computer software products are stored in a storage medium, and include several instructions to make A piece of equipment executes all or part of the methods of the various embodiments of the present disclosure.
- the aforementioned storage medium includes: various media that can store program codes such as U disk, mobile hard disk, read-only memory (Read Only Memory, ROM), magnetic disk or optical disk.
- embodiments of the present disclosure are not limited to any targeted combination of hardware and software.
- FIG. 9 is a schematic diagram of a hardware entity of a human-computer game device provided by an embodiment of the present disclosure. As shown in FIG. A computer program that can run on the processor 901. When the processor 901 executes the program, the steps in the method of any of the foregoing embodiments are implemented.
- the device 900 for collecting game coins on the game table may be the detection device described in any of the above-mentioned embodiments.
- the memory 902 stores computer programs that can run on the processor, the memory 902 is configured to store instructions and applications executable by the processor 901, and can also cache the processor 901 and various parts of the man-machine game device 900 to be processed or have been processed.
- the processed data for example, image data, audio data, voice communication data and video communication data
- FLASH flash memory
- RAM random access memory
- the processor 901 executes the program, the steps of any one of the human-computer game methods mentioned above are realized.
- the processor 901 generally controls the overall operation of the man-machine game device 900 .
- An embodiment of the present disclosure provides a computer storage medium, where one or more programs are stored on the computer storage medium, and the one or more programs can be executed by one or more processors to implement the man-machine game method in any of the above embodiments A step of.
- the embodiment of the present disclosure also provides a computer program product, the computer program product carries a program code, and the instructions included in the program code can be used to execute the steps of the man-machine game method described in the above method embodiment, please refer to the above method Example.
- the above-mentioned computer program product may be realized by hardware, software or a combination thereof.
- the computer program product is embodied as a computer storage medium, and in another optional embodiment, the computer program product is embodied as a software product, such as a software development kit (Software Development Kit, SDK) and the like.
- the above-mentioned processor can be an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a digital signal processor (Digital Signal Processor, DSP), a digital signal processing device (Digital Signal Processing Device, DSPD), a programmable logic device (Programmable Logic At least one of Device, PLD), Field Programmable Gate Array (Field Programmable Gate Array, FPGA), Central Processing Unit (Central Processing Unit, CPU), controller, microcontroller, microprocessor. It can be understood that the electronic device implementing the above processor function may also be other, which is not limited in this embodiment of the present disclosure.
- the above-mentioned computer storage medium/memory can be read-only memory (Read Only Memory, ROM), programmable read-only memory (Programmable Read-Only Memory, PROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, EPROM), Electrically Erasable Programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), Magnetic Random Access Memory (Ferromagnetic Random Access Memory, FRAM), Flash Memory (Flash Memory), Magnetic Surface Memory, CD-ROM, or CD-ROM (Compact Disc Read-Only Memory, CD-ROM) and other memories; it can also be various terminals including one or any combination of the above-mentioned memories, such as mobile phones, computers, tablet devices, personal digital assistants, etc. .
- references throughout the specification to "one embodiment” or “an embodiment” or “embodiments of the present disclosure” or “previous embodiments” or “some embodiments” mean the target features related to the embodiments, A structure or characteristic is included in at least one embodiment of the present disclosure.
- appearances of "in one embodiment” or “in an embodiment” or “embodiments of the disclosure” or “the foregoing embodiments” or “some embodiments” throughout the specification are not necessarily referring to the same embodiments .
- the features, structures or characteristics of these objects may be combined in any suitable manner in one or more embodiments.
- sequence numbers of the above-mentioned processes do not mean the order of execution, and the execution order of the processes should be determined by their functions and internal logic, rather than by the embodiments of the present disclosure.
- the implementation process constitutes any limitation.
- the serial numbers of the above-mentioned embodiments of the present disclosure are for description only, and do not represent the advantages and disadvantages of the embodiments.
- the detection device executes any step in the embodiments of the present disclosure, and may be a processor of the detection device executes the step. Unless otherwise specified, the embodiments of the present disclosure do not limit the order in which the detection device performs the following steps. In addition, the methods for processing data in different embodiments may be the same method or different methods. It should also be noted that any step in the embodiments of the present disclosure can be executed independently by the detection device, that is, when the detection device executes any step in the above embodiments, it may not depend on the execution of other steps.
- the disclosed devices and methods may be implemented in other ways.
- the device embodiments described above are only illustrative.
- the division of the units is only a logical function division.
- the mutual coupling, or direct coupling, or communication connection between the various components shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms. of.
- the units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed to multiple network units; Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
- each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may be used as a single unit, or two or more units may be integrated into one unit; the above-mentioned integration
- the unit can be realized in the form of hardware or in the form of hardware plus software functional unit.
- the above-mentioned integrated units of the present disclosure are implemented in the form of software function parts and sold or used as independent products, they can also be stored in a computer-readable storage medium.
- the computer software products are stored in a storage medium, and include several instructions to make
- a computer device which may be a personal computer, a detection device, or a network device, etc.
- the aforementioned storage medium includes various media capable of storing program codes such as removable storage devices, ROMs, magnetic disks or optical disks.
- the embodiment of the present disclosure discloses a method, device, device, and storage medium for man-machine game play, wherein the method includes: recording the move positions of the first party and the second party during the game play process, and obtaining historical move record; responding to The first party's move event in the current round generates the second move strategy corresponding to the second party based on the current move position corresponding to the move event and the historical move record; the second move strategy includes multiple A second candidate position and the second party's winning rate corresponding to each second candidate position; based on the historical record and the current position, determine the chess strength of the first party in the current round value; the chess power quantization value is used to characterize the chess power level of the first party; in the plurality of second positions to be selected, the target placement position is determined; the second party winning rate corresponding to the target placement position is related to the chess power Quantized values match.
- the virtual user's move strategy can be dynamically adjusted, so that the virtual user's chess skill level can be dynamically matched with the real user's chess skill level, so that the real user can play the game
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Abstract
Description
Claims (21)
- 一种人机对弈方法,所述方法包括:在对弈过程中,记录第一方和第二方的落子位置,得到历史落子记录;响应于所述第一方在当前回合的落子事件,基于所述落子事件对应的当前落子位置和所述历史落子记录,生成所述第二方对应的第二落子策略;所述第二落子策略包括多个第二待选位置和每一所述第二待选位置对应的第二方胜率;基于所述历史落子记录和所述当前落子位置,确定所述第一方在所述当前回合的棋力量化值;所述棋力量化值用于表征所述第一方的棋力水平;在所述多个第二待选位置中确定目标落子位置;所述目标落子位置对应的第二方胜率与所述棋力量化值匹配。
- 根据权利要求1所述的方法,其中,所述基于所述历史落子记录和所述当前落子位置,确定所述第一方的棋力量化值,包括:将所述历史落子记录和所述当前落子位置输入至预设的棋力评测模型,得到所述第一方的棋力评分;所述棋力评分用于表征所述第一方在对弈开始至所述当前回合的整体棋力水平;基于所述第一方的棋力评分,确定所述第一方的棋力量化值。
- 根据权利要求2所述的方法,其中,所述在所述多个第二待选位置中确定目标落子位置,包括:基于每一所述第二待选位置对应的第二方胜率,对所述多个第二待选位置进行排序,确定每一所述第二待选位置的排序位置;根据预设的第一映射表,获取所述第一方的棋力评分对应的目标排序位置;所述第一映射表包括棋力评分与排序位置的映射关系;将所述目标排序位置对应的第二待选位置确定为所述目标落子位置。
- 根据权利要求2所述的方法,其中,所述在所述多个第二待选位置中确定目标落子位置,包括:根据预设的第二映射表,获取所述第一方的棋力评分对应的目标胜率区间;基于所述目标胜率区间,将位于所述目标胜率区间中的第二待选位置确定为所述目标落子位置。
- 根据权利要求1所述的方法,其中,在所述响应于所述第一方在当前回合的落子事件,基于所述落子事件对应的第一当前落子和所述历史落子记录,生成所述第二方对应的第二落子策略之前,所述方法还包括:基于所述历史落子记录,预测所述第一方对应的第一落子策略;所述第一落子策略包括多个第一待选位置和每一所述第一待选位置对应的第一方胜率;所述基于所述历史落子记录和所述当前落子位置,确定所述第一方的棋力量化值,包括:基于每一所述第一待选位置对应的第一方胜率,确定所述当前落子位置对应的第一方胜率;将所述当前落子位置对应的第一方胜率确定为所述棋力量化值。
- 根据权利要求5所述的方法,其中,所述在所述多个第二待选位置中确定目标落子位置,包括:基于所述当前落子位置对应的第一方胜率,在所述多个第二待选位置中确定目标落子位置;所述目标落子位置的第二方胜率与所述第一方胜率存在映射关系。
- 根据权利要求1至6所述的方法,其中,所述历史落子记录包括落子时间;所述方法还包括:基于所述历史落子记录,获取所述第一方的平均落子时长;所述第一方的平均落子时长用于表征所述第一方在所述第二方落子后的落子速度;在所述第一方的平均落子时长满足预设条件的情况下,基于所述历史落子记录,预测 所述第一方在所述当前回合的第三落子策略;所述第三落子策略包括多个第三待选位置;所述第三待选位置与所述第一方在历史回合的棋力量化值相关;针对每一所述第三待选位置,基于所述第三待选位置和所述历史落子记录,生成所述第二方对应的第四落子策略;所述第四落子策略包括多个第四待选位置和每一所述第四待选位置对应的第二方胜率;响应于所述第一方在当前回合的落子事件,基于所述落子事件对应的当前落子位置在每一所述第三待选位置对应的第四落子策略中获取所述第二落子策略。
- 根据权利要求7所述的方法,其中,所述基于所述历史落子记录,获取所述第一方的平均落子时长,包括:基于所述历史落子记录中所述第一方的至少一个落子时间和所述第二方的至少一个落子时间,确定至少一个第一时间间隔;所述第一时间间隔为所述第二方落子的落子时间,与相邻的所述第一方落子的落子时间之间的时间间隔;基于所述至少一个第一时间间隔,生成所述第一方的平均落子时长。
- 根据权利要求1至8所述的方法,其中,所述方法还包括:获取所述第一方在历史回合的棋力量化值;基于所述第一方在所述历史回合的棋力量化值和所述第一方在所述当前回合的棋力量化值,生成提示信息;所述提示信息用于表征所述第一方在不同回合的棋力变化情况。
- 一种人机对弈装置,包括:记录部分,被配置为在对弈过程中,记录第一方和第二方的落子位置,得到历史落子记录;生成部分,被配置为响应于所述第一方在当前回合的落子事件,基于所述落子事件对应的当前落子位置和所述历史落子记录,生成所述第二方对应的第二落子策略;所述第二落子策略包括多个第二待选位置和每一所述第二待选位置对应的第二方胜率;确定部分,被配置为基于所述历史落子记录和所述当前落子位置,确定所述第一方在所述当前回合的棋力量化值;所述棋力量化值用于表征所述第一方的棋力水平;落子部分,被配置为在所述多个第二待选位置中确定目标落子位置;所述目标落子位置对应的第二方胜率与所述棋力量化值匹配。
- 根据权利要求10所述的装置,其中,所述确定部分,还被配置为:将所述历史落子记录和所述当前落子位置输入至预设的棋力评测模型,得到所述第一方的棋力评分;所述棋力评分用于表征所述第一方在对弈开始至所述当前回合的整体棋力水平;基于所述第一方的棋力评分,确定所述第一方的棋力量化值。
- 根据权利要求11所述的装置,其中,所述落子部分,还被配置为:基于每一所述第二待选位置对应的第二方胜率,对所述多个第二待选位置进行排序,确定每一所述第二待选位置的排序位置;根据预设的第一映射表,获取所述第一方的棋力评分对应的目标排序位置;所述第一映射表包括棋力评分与排序位置的映射关系;将所述目标排序位置对应的第二待选位置确定为所述目标落子位置。
- 根据权利要求12所述的装置,其中,所述落子部分,还被配置为:根据预设的第二映射表,获取所述第一方的棋力评分对应的目标胜率区间;基于所述目标胜率区间,将位于所述目标胜率区间中的第二待选位置确定为所述目标落子位置。
- 根据权利要求10所述的装置,其中,在所述响应于所述第一方在当前回合的落子事件,基于所述落子事件对应的第一当前落子和所述历史落子记录,生成所述第二方对应的第二落子策略之前,所述生成部分,还被配置为:基于所述历史落子记录,预测所述第一方对应的第一落子策略;所述第一落子策略包括多个第一待选位置和每一所述第一待选位置对应的第一方胜率;所述确定部分,还被配置为:基于每一所述第一待选位置对应的第一方胜率,确定所述当前落子位置对应的第一方胜率;将所述当前落子位置对应的第一方胜率确定为所述棋力量化值。
- 根据权利要求14所述的装置,其中,所述落子部分,还被配置为:基于所述当前落子位置对应的第一方胜率,在所述多个第二待选位置中确定目标落子位置;所述目标落子位置的第二方胜率与所述第一方胜率存在映射关系。
- 根据权利要求10至15任一项所述的装置,其中,所述历史落子记录包括落子时间,所述生成部分,还被配置为:基于所述历史落子记录,获取所述第一方的平均落子时长;所述第一方的平均落子时长用于表征所述第一方在所述第二方落子后的落子速度;在所述第一方的平均落子时长满足预设条件的情况下,基于所述历史落子记录,预测所述第一方在所述当前回合的第三落子策略;所述第三落子策略包括多个第三待选位置;所述第三待选位置与所述第一方在历史回合的棋力量化值相关;针对每一所述第三待选位置,基于所述第三待选位置和所述历史落子记录,生成所述第二方对应的第四落子策略;所述第四落子策略包括多个第四待选位置和每一所述第四待选位置对应的第二方胜率;响应于所述第一方在当前回合的落子事件,基于所述落子事件对应的当前落子位置在每一所述第三待选位置对应的第四落子策略中获取所述第二落子策略。
- 根据权利要求16所述的装置,其中,所述生成部分,还被配置为:基于所述历史落子记录中所述第一方的至少一个落子时间和所述第二方的至少一个落子时间,确定至少一个第一时间间隔;所述第一时间间隔为所述第二方落子的落子时间,与相邻的所述第一方落子的落子时间之间的时间间隔;基于所述至少一个第一时间间隔,生成所述第一方的平均落子时长。
- 根据权利要求10至17任一项所述的装置,其中,所述生成部分,还被配置为:获取所述第一方在历史回合的棋力量化值;基于所述第一方在所述历史回合的棋力量化值和所述第一方在所述当前回合的棋力量化值,生成提示信息;所述提示信息用于表征所述第一方在不同回合的棋力变化情况。
- 一种人机对弈设备,包括:存储器和处理器,所述存储器存储有可在所述处理器上运行的计算机程序,所述处理器执行所述计算机程序时实现权利要求1至9任一项所述方法中的步骤。
- 一种计算机存储介质,所述计算机存储介质存储有一个或者多个程序,所述一个或者多个程序可被一个或者多个处理器执行,以实现权利要求1至9任一项所述方法中的步骤。
- 一种计算机程序产品,包括计算机可读代码,当所述计算机可读代码在电子设备中运行时,所述电子设备中的处理器执行用于实现权利要求1至9任一项所述方法中的步骤。
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