Information processing system, information processing device, program, and information processing method

Abstract

To provide an information processing system, an information processing device, a program, and an information processing method capable of increasing fun of a game.SOLUTION: An information processing system previously stores setting data including parameter variation condition information regarding the amount of variation of parameters when each game element is executed, and provides a game capable of executing a parameter increasing processing for increasing a predetermined parameter of a predetermined game medium on the basis of the setting data by execution of a game element based on a player's input information. The information processing system executes: model generation processing for generating a learned model by learning play history data regarding a player's parameter increasing processing; target information reception processing for receiving target information regarding parameters of a game medium from a player; and automatic play processing for automatically executing a game element selected based on a learned model from among multiple game elements according to target information.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an information processing system, an information processing device, a program, and an information processing method, particularly Information processing system, information processing device, program and information for executing information processing in a team - Patents.com It relates to a processing method. [Background technology]

[0002] For games that can be run on player devices such as smartphones and game consoles, Enhance characters and items that can be used in the game based on arbitrary conditions. It is known that some plants can be cultivated.

[0003] In Patent Document 1, events in the real world and the actions of players (e.g. the results of sports matches) are recorded. A technology that automatically develops characters based on information such as food, shopping, and travel. has been disclosed. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP2002-346216A Summary of the Invention [Problem to be solved by the invention]

[0005] The technology in Patent Document 1 depends on real-world events, so it cannot reflect the player's wishes. In games like this, which involve the development and strengthening of game media, There is a demand for games with highly entertaining features.

[0006] The present invention has been made in consideration of the above circumstances, and aims to improve the entertainment value of games. To provide an information processing system, an information processing device, a program, and an information processing method that can The objective of this study is to [Means for solving the problem]

[0007] In order to achieve the above object, an information processing system according to the present invention comprises: Parameter change conditions regarding the amount of parameter change when each game element is executed Setting data including the information is stored in advance, By executing game elements based on input information from a player, a predetermined A game in which a parameter increase process for increasing a predetermined parameter of the game medium can be executed An information processing system to be provided, The player's play history data regarding the parameter increase process is learned to create a learned model. A model generation process for generating a model A goal information regarding the parameter of the game medium is received from the player. Information reception process; Selecting from among a plurality of game elements based on the trained model in accordance with the goal information an automatic play process for automatically executing the game elements that are Run The model generation process includes: The state of the game medium and the game requirements executed until the state of the game medium after the execution By learning the game element execution information including the type of element and the number of executions, It generates a trained model.

[0008] In order to achieve the above object, an information processing device according to the present invention comprises: Parameter change conditions regarding the amount of parameter change when each game element is executed Setting data including the information is stored in advance, By executing game elements based on input information from a player, a predetermined A game in which a parameter increase process for increasing a predetermined parameter of the game medium can be executed An information processing device to be provided, The player's play history data regarding the parameter increase process is learned to create a learned model. A model generation process for generating a model A goal information regarding the parameter of the game medium is received from the player. Information reception process; Selecting from among a plurality of game elements based on the trained model in accordance with the goal information an automatic play process for automatically executing the game elements that are Run The model generation process includes: The state of the game medium and the game requirements executed until the state of the game medium after the execution By learning the game element execution information including the type of element and the number of executions, It generates a trained model.

[0009] The program according to the present invention for achieving the above object is: Parameter change conditions regarding the amount of parameter change when each game element is executed Setting data including the information is stored in advance, By executing game elements based on input information from a player, a predetermined A game in which a parameter increase process for increasing a predetermined parameter of the game medium can be executed The information processing device to be provided includes: The player's play history data regarding the parameter increase process is learned to create a learned model. A model generation process for generating a model A goal information regarding the parameter of the game medium is received from the player. Information reception process; Selecting from among a plurality of game elements based on the trained model in accordance with the goal information an automatic play process for automatically executing the game elements that are set; The model generation process includes: The state of the game medium and the game requirements executed until the state of the game medium after the execution By learning the game element execution information including the type of element and the number of executions, It generates a trained model.

[0010] In order to achieve the above object, an information processing method according to the present invention comprises the steps of: Parameter change conditions regarding the amount of parameter change when each game element is executed Setting data including the information is stored in advance, By executing game elements based on input information from a player, a predetermined A game in which a parameter increase process for increasing a predetermined parameter of the game medium can be executed The information processing device to be provided is The player's play history data regarding the parameter increase process is learned to create a learned model. A model generation process for generating a model A goal information regarding the parameter of the game medium is received from the player. Information reception process; Selecting from among a plurality of game elements based on the trained model in accordance with the goal information an automatic play process for automatically executing the game elements that are set; The model generation process includes: The state of the game medium and the game requirements executed until the state of the game medium after the execution By learning the game element execution information including the type of element and the number of executions, It generates a trained model. Effect of the Invention

[0011] According to this invention, the interest in the game is increased. [Brief description of the drawings]

[0012] [Figure 1] 1 is a block diagram illustrating an outline of a configuration of an information processing system according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a block diagram illustrating an outline of the configuration of an information processing device in the information processing system according to the present embodiment. [Diagram 3] FIG. 2 is a block diagram for explaining an outline of the functions of an information processing device in the information processing system according to the present embodiment. [Figure 4] FIG. 10 is a block diagram illustrating an outline of the configuration of a game-related information storage unit of the information processing system according to the present embodiment. [Diagram 5] 10 is a flowchart for explaining an outline of information processing in the information processing system according to the present embodiment. [Figure 6] FIG. 1 is a block diagram illustrating an outline of the configuration of a player terminal of the information processing system according to the present embodiment. [Figure 7] 10 is a flowchart outlining the processing of the information processing system according to the present embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Next, an information processing system according to an embodiment of the present invention will be described with reference to FIGS. Reveal.

[0014] FIG. 1 is a block diagram illustrating an outline of the configuration of an information processing system according to an embodiment of the present invention. As shown in the figure, the information processing system 10 includes an information processing device 20 and a plurality of players. The main components of the system include a user terminal 30 and a network N such as the Internet. The devices are connected so as to be accessible to each other.

[0015] In this embodiment, the information processing system 10 is an information processing device provided in a business operator 1. 20 generates objects that compose a game, which are composed of images, videos, sounds, etc. The information processing is executed by the player terminal 30 owned by the player 2. , and provides the game to the player terminal 30.

[0016] The games provided by the operator 1 in the information processing system 10 include, for example, battle games, puzzle games, etc. Games, action games, baseball games, soccer games, other sports games, quizzes Games, pinball games, card games, rhythm games, RPGs (role-playing games) games, location-based games, board games, adventure games, casino games, simulation games The games may be simulation games, strategy games, racing games, etc.

[0017] Next, a specific configuration of each unit of the information processing system 10 according to the present embodiment will be described.

[0018] In this embodiment, the information processing device 20 is a desktop or notebook computer. This is implemented by the

[0019] FIG. 2 is a block diagram illustrating an outline of the configuration of the information processing device 20. As shown in the figure, The information processing device 20 includes a processor 21, a memory 22, a storage 23, a transmission / reception unit 24, and and an input / output unit 25, which are electrically connected to each other via a bus .

[0020] The processor 21 controls the operation of the information processing device 20 and transmits and receives data between the various elements. The CPU is a computing device that controls communication and performs processing required to execute application programs.

[0021] In this embodiment, the processor 21 is, for example, a CPU (Central Processor). The data is stored in the storage 23 (described later) and expanded in the memory 22. The CPU 10 executes the application program and performs each process.

[0022] In this embodiment, the memory 22 is a dynamic random access memory (DRAM). It is implemented in a main memory consisting of a volatile memory device such as an ESS Memory.

[0023] The memory 22 is used as a working area for the processor 21, and is also used as a 0 boot time BIOS (Basic Input / Output System m), and various setting information, etc. are stored.

[0024] The storage 23 stores programs, information used for various processes, and the like.

[0025] The transmitting / receiving unit 24 connects the information processing device 20 to the network N. , Bluetooth (registered trademark) and BLE (Bluetooth Low Energy y) may be provided with a short-range communication interface.

[0026] The input / output unit 25 is connected to input / output devices such as a keyboard, a mouse, or a display. It is an interface that can be used.

[0027] The bus 26 connects the processor 21, the memory 22, the storage 23, the transceiver 24, and and the input / output unit 25, for example, address signals, data signals, and various control signals are transmitted. Reach.

[0028] FIG. 3 is a block diagram for explaining an outline of the functions of the information processing device 20. As shown in the figure, In this embodiment, the information processing device 20 includes a game processing unit 40, a game-related information storage unit 41, , a parameter increasing unit 42, a learning unit 43, a learned model storage unit 44, and a target information receiving unit 45. The device includes a goal information storage unit 46, a behavior setting unit 47, and an appearance changing unit 48.

[0029] The game-related information storage unit 41, the trained model storage unit 44, and the goal information storage unit 46 This is realized by partitioning the memory area of ​​the storage 23, and the game processing unit 40, the parameter A data increasing unit 42, a learning unit 43, a goal information receiving unit 45, a behavior setting unit 47, and an appearance changing unit 48 is realized by executing a program stored in the memory 22 by the processor 21. can be.

[0030] The game processing unit 40 performs basic processing of the game, such as game progression and character control. For example, various processes such as game progress and game mode switching are performed. Execute.

[0031] In this embodiment, the game processing unit 40 performs arbitrary information processing related to the game as an event. The events to be executed are, for example, the actions used in the game. Various in-game events (e.g., any character) where you can win game media such as items. It is assumed that the occasion will be a special event such as a character's birthday celebration.

[0032] FIG. 4 is a block diagram for explaining the outline of the configuration of the game-related information storage unit 41. In this way, the game-related information storage unit 41 stores game information D1, player information D2, game media, and Body information D3, game element information D4, and operation information D5 are stored.

[0033] The game information D1 is various data that is appropriately configured according to the type of game. For example, For games including quest games, the stage name and enemy name associated with the stage ID This includes the character's data and the stamina consumed data. It is consumed when a game is executed (for example, when a game element starts to be executed) and is consumed over time or when a specific item is executed. The amount of the lost time may be recovered by using the system, charging a fee, etc.

[0034] In this embodiment, the player information D2 includes a player name associated with a player ID, Player-related parameters such as level, owned characters, items, etc. Type of game media, level of each game media, attack power and other parameters, number, acquisition method, acquisition time time, number of items consumed, amount of paid or free in-game currency owned, points owned Number of points earned, amount charged, number of times lottery was played, total playing time, This includes data such as the play stage and the number of enemies defeated.

[0035] Furthermore, in this embodiment, the player information D2 includes play history data. The play history data may include any of the game elements described below for any game medium. Using the method, how much (number of times each game element is executed, execution time (including time), execution frequency) Which parameters of the game media were increased by how much (e.g., numerical increase) or the game In the game, player 2 changes the appearance of the game medium (evolution), The play history data includes information about the history of training (including strengthening, evolution, etc.) of For example, the quests that the player actually performed to increase the attack power of a specific character, etc. Increases certain parameters of a certain game medium, such as game elements and information on items used The play history data can store information about game elements executed to play the game. Contains information associated with the execution of all game elements. For example, Start time, end time, time spent from start to end, and time spent by game elements Items consumed, in-game currency, points, and the state of the game media before and after the execution of game elements This includes information on the state (various parameters such as level) and changes to the game medium.

[0036] Data on owned items includes possession of one or more paid items and free items Contains data about the number of items owned, associated with the IDs of the items owned, etc. Contains data on:

[0037] Data on the play stage is the number of stages set up and which one Player 2 played. Data about stages you have played up to now, such as number of times played, cleared This includes data such as:

[0038] In this embodiment, the game medium information D3 includes information about the characters owned by the player 2, the game Game media such as background images, items, etc., or in-game currency used within the game Contains data on

[0039] Data related to game media such as characters owned may include, for example, the ID of each character The acquisition date and time, character name, level, rarity, HP (current value / maximum value) associated with ), attributes, skills, attack power (current value / maximum value), defense power (current value / maximum value), frequency of use, etc. It includes various parameters such as:

[0040] The acquisition date and time may be, for example, when a character is assigned to the player 2 through the progress of the game or the execution of a lottery. The rarity of a character is, for example, the number of characters in a lottery. This is data regarding the probability of winning.

[0041] For example, HP, attack power, and defense power include the current value, i.e., "current value" and This includes the "maximum value" when the character is trained to the maximum level. The upper limit of various parameters related to the game media is set based on the use of specific items, charges, and player levels. Increases depending on conditions such as the number of times the game is played, the time spent playing, the number of logins, and the time spent logging in. Alternatively, it may be set to decrease.

[0042] For example, in a battle game, the attributes may be fire, water, or wind. In sports games, the classification indicates the strengths of the character. This includes classifications indicating positions, etc., and other data regarding the setting of character classifications.

[0043] Skills are data about the special skills a character can use, and their frequency of use is , data regarding how frequently Player 2 has selected or used that character in the past. This frequency of use is calculated over the entire period since Player 2 started the game. Alternatively, it may be calculated over an arbitrary period such as the most recent few months.

[0044] In this embodiment, the data on the parameter includes the parameter increase (or decrease). The conditions under which a game is played (for example, which game element is executed, which parameter of which game media is executed, The conditions for determining whether the game content is increased or not and the thresholds for changing the appearance of the game content, which will be described later, are specified. The setting data is added as metadata. The parameter variation condition information includes parameter variation amount information regarding the parameter variation amount when the above is executed.

[0045] In this embodiment, the condition for the parameter to increase is, for example, when a character The parameter is calculated by the amount of increase in the parameter when a certain game element is executed. The correlation between characters and game elements regarding the increase in data is specified.

[0046] Data on items owned by player 2 included in the game medium information D3 may include, for example, For example, the number of items owned by Player 2 and other data associated with the ID of the item are stored. Items include recovery items used in the game, items that lower enemy abilities, etc. Items, weapons, armor, accessories, vehicles, or parameters worn by characters Each item has conditions for use, and what happens when you use it (when wearing it). The effects of the function, etc. are stored in association with each other.

[0047] In this embodiment, the game element information D4 includes quests, missions, exploration, battles, and training. Events (game elements) that are executed within the game, such as synthesis, story or lottery In this embodiment, the data is obtained by executing these game elements. As a result, a certain parameter of a predetermined game medium is increased or the appearance is changed. In addition, as a game element, there are parameters such as "development materials". This may also include the use of items that increase the meter (parameter increase items). The control is associated with the item depending on the player's use of the item. Each game element increases the parameter by a preset amount. The consumption element is, for example, time. , stamina, items, in-game currency, in-game points, etc.

[0048] A quest is an adventure (including multiple stages) involving battles set in the game. The missions are data related to various tasks set in a game, for example. For example, exploration is data that is generated over time by exploring a specific area without combat. Therefore, the data is about what you can get rewards for, and the battle is based on the instructions of other players. Data on a battle against an enemy character controlled by the user or automatically by the system. For example, character training can be done directly (increasing parameters). This is data on the

[0049] Synthesis is the process of combining multiple game media to create a new game media. Combining any one character with any other character to create a new character You can also combine any one item with any other item to create a new item. This is data about synthesis.

[0050] Furthermore, the story is the data about reading the story, and the lottery is the data about playing. This is data about the characters used by Ya2 in the game drawing lots. Each game element is associated with information about the increase in game parameters. When the layer selects and executes each game element, the control unit (parameter increase unit) The predetermined parameter of the game media is increased (or decreased).

[0051] The operation information D5 is operation information input from the player terminal 30. Input time information when the operation information is input is included in 0. This operation information D5 includes, for example, The start of the recording starts when the game starts on the player terminal 30. Operation information up to the recording end time when the recording is to be ended, or From the recording start time when the recording start command is input to the recording end time when the recording end command is input Contains operation information.

[0052] The parameter increase unit 42 shown in FIG. 3 increases the parameter by executing game elements based on input information from the player. Thus, a process of increasing a predetermined parameter of a predetermined game medium based on the setting data is performed. In this embodiment, any game element is executed (parameter increase process). As a result, a specific parameter of a specific game medium increases.

[0053] In this embodiment, the learning unit 43 uses the play history data and A model trained using machine learning techniques based on the setting data included in the game media information D3 The process of generating a model is executed (model generation process).

[0054] In addition, the play history data is machine-learned using only the play history data of the first player, player 2. Alternatively, machine learning may be performed using the play history data of multiple other players 2. Good too.

[0055] FIG. 5 is a flowchart for explaining an outline of the process of the learning unit 43. As shown in the figure, In step S1, play history data and setting data are accumulated as learning data, and In step S2, machine learning is performed on the accumulated training data to generate a trained model. The setting data is set in advance by the service provider (system administrator) and stored in the storage unit. The play history data is data relating to the play history of each player who has executed the game. It's data.

[0056] The learning unit 43 is a device that learns a game corresponding to a predetermined target information (input data) and the target information. The model is trained using training data that is a set of information on the system elements (output data). The model generation process uses play history as known learning data. The parameter information of the game medium after the execution of a predetermined game element in the data is input to the input device. game element including at least one of the following information: The execution information is associated with output data and a trained model is generated. In addition to the learning data mentioned above, game-related information such as game specifications and in-game rules is also included. The learning unit 43 may learn the basic information from the play history data. It is possible to extract information corresponding to input data and output data. The learning unit 43 determines whether the character A (game medium A) is a character B (game medium B) by executing the game elements from the play history data. The learning unit 43 extracts information (target information) when the level of the learning information (target information) reaches level 100. For example, if character A goes from a certain state (level 1, level 10, etc.) to a level The game elements performed to reach 100 ("Use character A to complete quest A for 5 minutes" "Use character A to complete quest B twice and quest C four times," etc.) The game element information corresponding to one goal is extracted as the game element information. The learning unit 43 learns the execution history of the game elements from the play history data. (Which game element was executed and how many times using which game medium) and execution result information (which Which parameters of the game media fluctuate to what degree, and what values ​​the parameters take as a result The learning unit 43 can extract such execution results and store them in association with each other. The result information is extracted as goal information, and the corresponding game element information (game element execution history) is It is possible to extract the game elements (history information) and learn them as a set. The amount of stamina, items, in-game currency, and each game element consumed during the game The time it takes to complete the training (time spent), the state of the game media after the training (level, attack power, defense Also include information such as the total number of executions of game elements required to reach a certain level (e.g., power), execution time, etc. The information may be extracted, associated, and stored, or used to generate a learning model. inputting target information regarding target parameters of one or more game media such as characters; In response to this, the type of game element to be executed and the number of executions, etc., to reach the target information are output. The model is trained to obtain the power required to execute the game to reach the target information. If there are multiple patterns of the type and execution count of the game element, for example, the above consumption element information For example, if the first priority is given to the time spent, In this case, the type of game element and the number of executions are selected so that the time consumption is minimized. The order of elements may be preset by the system or may be determined based on information input by the user. That is, for example, when receiving goal information, the priority of the consumption element may be selected. The user may select the game content. For example, by equipping weapons, armor, etc., or by executing game elements, Items that change parameters (item level, etc.) (recovery items, strengthening items, multipliers (e.g., transportation, etc.)

[0057] Machine learning is carried out by appropriately selecting learning data and learning algorithms. The machine learning method is not particularly limited as long as it can be learned. The neural network is trained using machine learning data, and the desired result is obtained when a certain input data is input. The parameters of the neural network are optimized so that the output data is In this example, a trained model is used to convert unknown input data (target information) into the corresponding Input the data into the trained model to obtain the desired output data (information on the game elements to be executed). Machine learning can be unsupervised learning, supervised learning, or reinforcement learning. It may be possible to use deep learning, neural networks, random Even if you use forest, SVM (Support Vector Machine), etc. Often, these machine learning techniques can be combined.

[0058] Next, in step S3, the generated trained model is converted into the trained model shown in FIG. The result is stored in the rule storage unit 44.

[0059] In this embodiment, the target information receiving unit 45 shown in FIG. The processing for receiving goal information regarding the goal to be set is executed (goal information receiving processing The received various input information, including the target information, is stored in the storage unit.

[0060] In this embodiment, the target information received in the target information receiving process is selected by the player 2. information on one or more game media selected by Player 2, and one or more parameters selected by Player 2 The information about the meter and the numerical value of the parameter selected by Player 2 are It includes at least one of them, or a combination of two or more of them.

[0061] The information on the game medium includes information on one or more specific game mediums selected by the player 2. The information on the game contents may or may not be included. Information selected by the player regarding whether the game content is owned or not owned The information about the game content may or may not include the attributes of the game content. The information about the game medium may or may not include information about the game medium. It may or may not include rarity information.

[0062] The information about the parameters is the type of parameter selected by Player 2 (e.g., level , offensive power, defensive power, etc.), or other information.

[0063] The information about the parameter values ​​is the parameter fluctuation range value selected by Player 2 ( For example, you want to increase your attack power by 10, your target value (you want to increase your defense power to 30, etc.), may include:

[0064] Next, in step S4, target information is accepted from the player.

[0065] In this embodiment, the goal information storage unit 46 stores goal information received from the player 2. It will be delivered.

[0066] Next, in step S5, an automatic training process (automatic play process) is executed, and target information By executing game elements selected by machine learning according to the game content, For example, after receiving the goal information, the player may select whether to start automatic training. Alternatively, the input information may be received to indicate the start of the operation, or the operation may be performed automatically on the condition that the target information is received. You may start training the animal.

[0067] In this embodiment, the behavior setting unit 47 uses machine learning based on the trained model. Select one or more game elements from among the multiple game elements, and The action setting unit 47 executes the game element once or multiple times. When target information D6 is received, any game element and its execution count are selected based on the trained model. and run the selected game element the selected number of times.

[0068] The action setting unit 47 determines whether or not a game element is consumed based on consumption element information consumed in the game in accordance with the execution of each game element. Based on the learned model, the game element selected based on the learned model is automatically executed. In other words, the action setting unit 47 executes a dynamic play process. In order to achieve this, the player can select one or more game elements and the number of times they are executed that are most efficient. Efficiency can be the shortest time, or the least amount of stamina, items, and games consumed. More specifically, the most important thing to achieve the goal information is The type and number of game elements that consume the least amount of time (including multiple combinations), Types and number of game elements that reduce tamina, and the game that consumes the least number of items The types and frequency of game elements that consume the least amount of in-game currency. It is also possible to output a plurality of patterns, or one of the patterns. When the user selects one of the patterns, the multiple patterns are presented to the user, and then the user is prompted to select the pattern. The action setting unit 47 may select one of the patterns. In order to do so, consumption factors (time, stamina, items, in-game currency, in-game points, etc.) A pattern in which one of the following is the smallest, or the total number of consumption elements of a given set of consumption elements is the smallest. The types of consumption elements used to determine such game elements may be selected from the following: The target information may be selected by the player or may be previously determined and stored. The address may be stored in the address space.

[0069] The action setting unit 47 sets the current player's level, experience points, and other parameters, The parameters of each game medium such as Kuta, level, attack power, etc., and the currently held in-game events Events (limited-time lottery events, quests, stories, etc.) and other game situations The game elements to be executed and the number of times each element is executed can be selected. That is, the action setting unit 47 may set the current game situation (for example, the level of character A) The difference (character A's level is 1) is compared with the target information (character A's level is 6) Based on the above, the game elements to be executed and the execution times of each game element are Specifically, the action setting unit 47 can select, for example, "Use character A. "Use character A to complete quest A 5 times", "Use character A to complete limited quest 1 time", "Use character "Proceed through story A to evolve character A until A reaches level 100" or In games, such as "combine character A and character B to create character C" You can set the action to be performed and select one or more game elements from among multiple game elements. Select the number and, if necessary, the target state (e.g., up to level 100).

[0070] In this embodiment, the appearance change unit 48 shown in FIG. The meter meets a predefined condition (e.g., a parameter reaches a certain threshold). When the game is started or exceeds a threshold, a process is executed to change the appearance of the game content. (Appearance change process).

[0071] This appearance change process changes, for example, the shape, size, color, etc. of the game medium. Alternatively, the weapons and clothes worn by the character in the game medium may be changed. It may be a method that involves various modifications. As data increases, not only will the appearance change, but any new skills will also be acquired and can be learned. Adding abilities or functions such as increasing the number of usable items or weapons, lifting restrictions, Changes in the upper and lower limits set for various parameters, such as increases or decreases, and combinations of these It may involve a combination.

[0072] The game processing unit 40, the game-related information storage unit 41, the parameter increasing unit 42, and the learning unit 43, learned model storage unit 44, goal information receiving unit 45, goal information storage unit 46, behavior setting In this embodiment, based on the processing in the appearance changing unit 47 and the appearance changing unit 48, The game is executed in the

[0073] In this embodiment, the player terminal 30 shown in FIG. 1 is a smartphone, which is a portable information terminal. It is implemented on a variety of devices, including game consoles, tablet computers, and desktop computers. It may be implemented by a laptop or notebook computer.

[0074] FIG. 6 is a block diagram illustrating an outline of the configuration of the player terminal 30. As shown in the figure, The player terminal 30 includes a control unit 31 and a display 32 as main components. The present invention may also include:

[0075] In this embodiment, the control unit 31 controls a player such as a display 32 and a camera (not shown). It controls each part of the terminal 30, such as the processor, memory, storage, transmission and reception It is composed of members such as the faith section.

[0076] In this embodiment, the control unit 31 includes a game application or a web site. The browser that can view the data is stored, and the data is displayed based on the processing of the program in the information processing device 20. The game is played on the player terminal 30 via a game application or a browser. The program is executed.

[0077] In this embodiment, the display 32 displays an image of the game being executed on the player terminal 30. The interface etc. is displayed.

[0078] The display 32 is a so-called touch panel that accepts information input by touching the display surface. touch panels implemented using various technologies such as resistive and capacitive touch panels .

[0079] In this embodiment, the operation information D5 is input via the display 32. The game information D5 is input regarding the operation and movement of the character used by the player 2 in the game. This is information that can be used.

[0080] The operation information D5 is an arbitrary operation of the player 2 on the display 32 (for example, tapping the screen). You can also move the cursor over the screen by clicking or swiping, or dragging and dropping icons displayed on the screen. The input is based on the action to be taken, etc.

[0081] Next, an overview of the processing of the information processing system 10 according to the present embodiment will be described.

[0082] FIG. 7 is a flow chart for explaining an outline of the processing of the information processing system 10 according to the present embodiment. As shown in the figure, first, in step S10, Target information is received from player 2 (target information receiving process).

[0083] When the target information is received, in the next step S11, Acquire game status information (game progress, type of characters owned, current parameters To organize the game state, for example, Based on the received goal information and the organized game state, the current game state is calculated. The difference between the target and the target set in the target information is calculated. Meter (Character A's target level is 10) and the current value of that character (Character A's Calculate the difference (+5) from the current level (5).

[0084] In step S12, the action in the game is set based on the arrangement of the game state. Select one or more game elements from among multiple game elements, and Execute.

[0085] When the selected game element is executed, in step S13, parameters according to the goal information are Basically, the parameters are increased until the target information is reached. The data execution process is executed, but the process may be terminated before reaching the target information. For example, meeting predefined stopping conditions such as lack of stamina or lack of items. In the parameter increase process, the parameter may be stopped by When the threshold is exceeded, in step S14, the appearance of the game content is changed (appearance change change process).

[0086] In this way, game elements are selected according to the goal information received from player 2, and the selected By executing the game elements, the parameters will increase. The appearance of the game media may be changed when a desired threshold is exceeded.

[0087] Therefore, it is important to ensure that actions aimed solely at increasing parameters are not repeated. This increases the interest in the game.

[0088] The present invention is not limited to the above-described embodiment, and may be modified without departing from the spirit and scope of the invention. Various modifications are possible.

[0089] In the above embodiment, the description has been given on the assumption that a single trained model is generated. However, for example, a trained model is generated for each of the multiple players 2. You may do so.

[0090] In the above embodiment, the program stored in the information processing device 20 stores information related to the game. The case where the information processing is executed has been described. The program may be configured to process information about the game on the player terminal 30. .

[0091] The present invention has the following configuration. (Item 1) Parameter fluctuations regarding the amount of parameter fluctuation when each game element is executed Setting data including condition information is stored in advance, By executing game elements based on input information from a player, a predetermined A game in which a parameter increase process for increasing a predetermined parameter of the game medium can be executed An information processing system to be provided, The player's play history data regarding the parameter increase process is learned to create a learned model. A model generation process for generating a model A goal information regarding the parameter of the game medium is received from the player. Information reception process; Selecting from among a plurality of game elements based on the trained model in accordance with the goal information an automatic play process for automatically executing the game elements that are Run The model generation process includes: The state of the game medium and the game requirements executed until the state of the game medium after the execution By learning the game element execution information including the type of element and the number of executions, Generate a trained model. Information processing system. (Item 2) The trained model is configured to receive the target information and generate a model corresponding to the target information. A learning device that outputs information on the type of game element and the number of executions required to reach the state of the game medium. 2. The information processing system according to item 1, which is a trained model. (Item 3) The trained model is The information processing system according to item 1 or 2, wherein the information processing system is generated for each of the players. . (Item 4) The target information is Item 1 or 2 including information about one or more of the game media selected by the player 3. An information processing system according to claim 2. (Item 5) The target information is information regarding the type of one or more of the parameters selected by the player; An information processing system according to item 1 or 2. (Item 6) The target information is Item 1 or 2 includes information regarding the numerical value of the parameter selected by the player. The information processing system described herein. (Item 7) The execution of the game element includes: Quests, battles, training, synthesis, story or lottery execution, or parameters The information processing system according to item 1 or 2, including at least one of the use of a promotion item. . (Item 8) 3. The information processing system according to item 1 or 2, wherein the game medium is a character. (Item 9) The model generation process includes: The play history data of the plurality of players is learned to generate the learned model. 3. An information processing system according to claim 1 or 2. (Item 10) When the parameter satisfies a predetermined condition by the parameter increase process, 3. The information processing system according to item 1 or 2, which executes an appearance change process for changing the appearance of the medium. Tem. (Item 11) The automatic play process performs the following in response to a difference between the target information and current game situation information: Item 1, or automatically executing the game element selected based on the trained model. 2. An information processing system according to claim 2. (Item 12) The automatic play process further includes: Based on element information, the game element selected based on the trained model is automatically 3. The information processing system according to item 1 or 2, (Item 13) Parameter fluctuations regarding the amount of parameter fluctuation when each game element is executed Setting data including condition information is stored in advance, By executing game elements based on input information from a player, a predetermined A game in which a parameter increase process for increasing a predetermined parameter of the game medium can be executed An information processing device to be provided, The player's play history data regarding the parameter increase process is learned to create a learned model. A model generation process for generating a model A goal information regarding the parameter of the game medium is received from the player. Information reception process; Selecting from among a plurality of game elements based on the trained model in accordance with the goal information an automatic play process for automatically executing the game elements that are Run The model generation process includes: The state of the game medium and the game requirements executed until the state of the game medium after the execution By learning the game element execution information including the type of element and the number of executions, Generate a trained model. Information processing device. (Item 14) Parameter fluctuations regarding the amount of parameter fluctuation when each game element is executed Setting data including condition information is stored in advance, By executing game elements based on input information from a player, a predetermined A game in which a parameter increase process for increasing a predetermined parameter of the game medium can be executed The information processing device to be provided includes: The player's play history data regarding the parameter increase process is learned to create a learned model. A model generation process for generating a model A goal information regarding the parameter of the game medium is received from the player. Information reception process; Selecting from among a plurality of game elements based on the trained model in accordance with the goal information an automatic play process for automatically executing the game elements that are set; The model generation process includes: The state of the game medium and the game requirements executed until the state of the game medium after the execution By learning the game element execution information including the type of element and the number of executions, Generate a trained model. program. (Item 15) Parameter fluctuations regarding the amount of parameter fluctuation when each game element is executed Setting data including condition information is stored in advance, By executing game elements based on input information from a player, a predetermined A game in which a parameter increase process for increasing a predetermined parameter of the game medium can be executed The information processing device to be provided is The player's play history data regarding the parameter increase process is learned to create a learned model. A model generation process for generating a model A goal information regarding the parameter of the game medium is received from the player. Information reception process; Selecting from among a plurality of game elements based on the trained model in accordance with the goal information an automatic play process for automatically executing the game elements that are set; The model generation process includes: The state of the game medium and the game requirements executed until the state of the game medium after the execution By learning the game element execution information including the type of element and the number of executions, Generate a trained model. Information processing methods. [Explanation of symbols]

[0092] 1 Operator 2 Players 10. Information Processing Systems 20 Information processing device 30 Player terminal

Claims

1. Parameter fluctuations regarding the amount of parameter fluctuation when each game element is executed Setting data including condition information is stored in advance, By executing game elements based on input information from a player, a predetermined A game in which a parameter increase process for increasing a predetermined parameter of the game medium can be executed An information processing system to be provided, The player's play history data regarding the parameter increase process is learned to create a learned model. A model generation process for generating a model A goal information regarding the parameter of the game medium is received from the player. Information reception process; Selecting from among a plurality of game elements based on the trained model in accordance with the goal information an automatic play process for automatically executing the game elements that are Run The model generation process includes: The state of the game medium and the game requirements executed until the state of the game medium after the execution By learning the game element execution information including the type of element and the number of executions, Generate a trained model. Information processing system.

2. The trained model is configured to receive the target information and generate a model corresponding to the target information. A learning device that outputs information on the type of game element and the number of executions required to reach the state of the game medium. The information processing system of claim 1 , wherein the model is a trained model.

3. The trained model is The information processing system according to claim 1 or 2, wherein the information processing system is generated for each of the players. Hmm.

4. The target information is 2. The game content selection method according to claim 1, further comprising:

3. The information processing system according to claim 2.

5. The target information is information regarding the type of one or more of the parameters selected by the player.

3. The information processing system according to claim 1 or 2.

6. The target information is 3. The method according to claim 1, further comprising: An information processing system according to the present invention.

7. The execution of the game element includes: Quests, battles, training, synthesis, story or lottery execution, or parameters The information processing system according to claim 1 or 2, further comprising at least one of a user and a user of a user-selected item. Hmm.

8. The information processing system according to claim 1 or 2, wherein the game medium is a character.

9. The model generation process includes: The play history data of the plurality of players is learned to generate the learned model.

3. The information processing system according to claim 1 or 2.

10. When the parameter satisfies a predetermined condition by the parameter increase process, 3. The information processing system according to claim 1, further comprising: an appearance change process for changing the appearance of the medium. Stem.

11. The automatic play process performs the following in response to a difference between the target information and current game situation information: The game element selected based on the trained model is automatically executed.

2. An information processing system according to claim 2.

12. The automatic play process further includes: Based on element information, the game element selected based on the trained model is automatically The information processing system according to claim 1 or 2,

13. Parameter fluctuations regarding the amount of parameter fluctuation when each game element is executed Setting data including condition information is stored in advance, By executing game elements based on input information from a player, a predetermined A game in which a parameter increase process for increasing a predetermined parameter of the game medium can be executed An information processing device to be provided, The player's play history data regarding the parameter increase process is learned to create a learned model. A model generation process for generating a model A goal information regarding the parameter of the game medium is received from the player. Information reception process; Selecting from among a plurality of game elements based on the trained model in accordance with the goal information an automatic play process for automatically executing the game elements that are Run The model generation process includes: The state of the game medium and the game requirements executed until the state of the game medium after the execution By learning the game element execution information including the type of element and the number of executions, Generate a trained model. Information processing device.

14. Parameter fluctuations regarding the amount of parameter fluctuation when each game element is executed Setting data including condition information is stored in advance, By executing game elements based on input information from a player, a predetermined A game in which a parameter increase process for increasing a predetermined parameter of the game medium can be executed The information processing device to be provided includes: The player's play history data regarding the parameter increase process is learned to create a learned model. A model generation process for generating a model A goal information regarding the parameter of the game medium is received from the player. Information reception process; Selecting from among a plurality of game elements based on the trained model in accordance with the goal information an automatic play process for automatically executing the game elements that are set; The model generation process includes: The state of the game medium and the game requirements executed until the state of the game medium after the execution By learning the game element execution information including the type of element and the number of executions, Generate a trained model. program.

15. Parameter fluctuations regarding the amount of parameter fluctuation when each game element is executed Setting data including condition information is stored in advance, By executing game elements based on input information from a player, a predetermined A game in which a parameter increase process for increasing a predetermined parameter of the game medium can be executed The information processing device to be provided is The player's play history data regarding the parameter increase process is learned to create a learned model. A model generation process for generating a model A goal information regarding the parameter of the game medium is received from the player. Information reception process; Selecting from among a plurality of game elements based on the trained model in accordance with the goal information an automatic play process for automatically executing the game elements that are set; The model generation process includes: The state of the game medium and the game requirements executed until the state of the game medium after the execution By learning the game element execution information including the type of element and the number of executions, Generate a trained model. Information processing methods.

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