Method and System for Replicating and Educating a Game Player

Abstract

Provided is a method and system for replicating a player playing a game similar to a game player and a method and system for instructing the game player in a game play method. According to the method of replicating the player and the method of instructing the player, the game player may receives an instruction how to play a game whose playing method is not well known to the game player. Also, as the player plays online games more than a predetermined number, a game playing engine of his own similar to himself may be made to play a game by proxy and the player can enjoy a team play game by forming a team with the game playing engine.

1 - 63 . (canceled)  
   
   
       64 . A method of replicating a game player's play of the game, comprising the steps of: 
 allowing a game player to install an automatic game engine in a game terminal;    receiving command data for a game from the game player while the game player is playing the game, the command data being associated with various game situations;    analyzing input tendency of the game player in playing the game for each game situation by utilizing said automatic game engine; and    configuring said automatic game engine based, at least in part, upon said analyzed input tendency data.    
   
   
       65 . The method of  claim 64 , wherein the step of analyzing input tendency data of the game player comprises the step of generating probability information with respect to the input for each of the analyzed game situations, and further comprising the step of providing a game level for the game player based, at least in part, upon the probability information.  
   
   
       66 . The method of  claim 65 , wherein, in the step of configuring according to the input tendency data, the probability information initialized in the automatic game engine is adjusted and updated by using the acquired input tendency probability.  
   
   
       67 . The method of  claim 64 , wherein in the step of analyzing input tendency data of the game player, a game play of a player at a game terminal is monitored at a predetermined time interval to acquire the input tendency data.  
   
   
       68 . The method of  claim 64 , wherein, in the step of analyzing the input tendency, input tendency probability information of the player is acquired based on the input performed by the player under each game situation by monitoring the game play of the player more than a specified number.  
   
   
       69 . The method of  claim 64 , wherein the step of receiving command data associated with various game situations from the game player comprises the step of receiving at least one command for replicating the game player via a user interface.  
   
   
       70 . The method of  claim 64 , wherein the automatic engine includes a database which includes data for a plurality of game players.  
   
   
       71 . The method of  claim 64 , wherein the game is a card game.  
   
   
       72 . The method of  claim 71 , further comprising the steps of: 
 monitoring the card game played by the player in response to the player's request; and    replicating betting tendency of the player by using the automatic game engine for replication, based upon the monitored data.    
   
   
       73 . The method of  claim 71 , wherein the automatic game engine for replication has initialized probability information on input for each game situation for basic game play, monitors card game play of the player, and adjusts and updates the initialized probability information according to input tendency probability information of the player based on the input tendency of the player in each game situation.  
   
   
       74 . The method of  claim 73 , wherein the step of replicating the card analysis tendency comprises the steps of: 
 comparing all sorts of betting conditions considering a betting order of the player, analysis of the cards of before and after competitors and betting state, the value of the cards of the player, the number of betting turns, and the progress of the card game and probability information of an opening bet of the automatic game engine for replication, with a certain bet performed by the player; and    adjusting upward or downward the card analysis tendency probability information of the automatic game engine, based on the frequency that the frequency of a certain betting of the player is higher than, lower than, and the same as the initialized bet of the automatic game engine for replication.    
   
   
       75 . The method of  claim 74 , wherein the frequency is computed by monitoring the card game playing of the player for recent n times.  
   
   
       76 . The method of  claim 73 , wherein in the step of replicating the card betting tendency, probability information of the bet of the automatic game engine for replication is adjusted based on the frequency of the certain bet performed under a certain betting situations by the player by using betting situations and the probability information of the initialized bet of the automatic game engine for replication according to the all sorts of the betting situation, considering the betting order of the player, the analysis on the cards of before and after competitors, the betting situation, and the progression of the card game.  
   
   
       77 . The method of  claim 76 , wherein the frequency is computed by monitoring the card game playing of the player for recent n times.  
   
   
       78 . The method of  claim 76 , in the case the card game played by the player is one of seven-card stud and seven-card stud high-low split that needs to select open cards, further comprising the step of replicating open card selection tendency in which the situation of all received cards, determined according to the kind of each game and the probability information of the initialized open card selecting motion of the automatic game engine according to the condition of the received card are updated by the probability based on the probability information of the open card selecting motion of the automatic game engine for replication based on the frequency of open card selecting motion performed in the case of each of the card received by the player.  
   
   
       79 . The method of  claim 76 , further comprising the step of replicating a card game habit of the player in playing the game, the step of replicating the card game habit comprising the steps of: 
 replicating a mandatory betting use habit in which probability information on a first betting habit of the player is updated based on the frequency that the player performs a raise betting in a first betting;    replicating a ping betting use habit in which probability information on the ping betting tendency of the player is updated based on the frequency that the player performs ping betting activity in the situation of not more than a second group of cards and a boss;    replicating a double betting use habit in which probability information on the double betting tendency of the player is updated based on the frequency that the player performs double betting activity in the situation of not more than a second grade group of cards and the ping betting existing in previous order; and    replicating response time use habit in which probability information on the response time use habit of the player is updated based on the average of response times used while the player    plays a game for each sort of games, wherein the response time average is computed by using at least one of time used in opening a card, time used for each betting, time used in changing a card, and time used in determining a direction.    
   
   
       80 . The method of  claim 76 , wherein, in the case a card game played by the player is a high-low selection type game, the frequency that the player determines a swing in each situation in which perfect first grade group of cards, a general first grade group of cards, and competitive first group of cards are combined with high, low, and high-low is computed and the probability information on the swing tendency of the player is set in the replication automatic game engine.  
   
   
       81 . A method of controlling an automatic game engine, comprising the steps of: 
 generating input tendency data by analyzing input tendency of a player with respect to various game situations while playing a game;    storing the generated input tendency data in association with the game situation in a database;    searching the stored input tendency data associated with a certain game situation in said database in the case an automatic game engine plays a game with respect to the certain game situation; and    enabling the automatic game engine to perform the game based, at least in part, upon the searched input tendency data.    
   
   
       82 . The method of  claim 81 , further comprising the steps of: 
 generating the difficulty information or style information associated with the game play of the automatic game engine with respect to the input tendency data; and    storing the generated difficulty information or style information in association with the input tendency data of the database, wherein, in the step of searching the one piece of the input tendency data, ability level or style of a player opposing the automatic game engine is checked, the difficulty information or style information corresponding to the checked ability level or player style of the player is identified from the database, and one piece of the input tendency data from the input tendency data corresponding to the identified difficulty information or the style information is randomly determined.    
   
   
       83 . The method of  claim 81 , wherein the step of generating the input tendency data comprises the steps of: 
 enabling the automatic game engine to play a game as a plurality of random player models, with respect to the game situation;    checking the result of each of the played game models; and    generating input tendency data by using the game model checked as a result satisfying a selected standard.    
   
   
       84 . The method of  claim 83 , wherein the result is determined to be either the correct answer or incorrect answer, and the automatic game engine uses the game model that is limited to either the correct answer or the incorrect answer with a predetermined error in the case the input tendency data is generated.  
   
   
       85 . The method of  claim 81 , further comprising the steps of: 
 determining difficulty information or style information with respect to the stored input tendency data and storing the difficulty information or style information in association with the determined input tendency data for each game situation in a predetermined database;    building an AI tool by using the searched input tendency data in the case a request for the AI tool including one of the difficulty information and the style information is received from a terminal of the player; and    installing the AI tool in the terminal in response to the AI tool request,    wherein the step of searching the stored input tendency data associated with a certain game situation comprises the step of searching the input tendency data corresponding to the difficulty information or the style information from the database.    
   
   
       86 . The method of  claim 85 , wherein the AI tool is installed in the terminal and controls a mini automatic game engine included in the terminal to play the game, and the mini automatic game engine determines one input tendency data associated with the game situation played by the mini automatic game engine from the input tendency data included in the AI tool and plays the game based on the determined input tendency data.  
   
   
       87 . The method of  claim 86 , wherein, in the step of building the AI tool, at least one input tendency data is identified by considering the game playing ability of the mini automatic game engine and the difficulty information of the input tendency data, and the AI tool is built by using the identified input tendency data, in which the game playing ability of the mini automatic game engine is divided into a high-skilled player, a middle-skilled player, and a low-skilled player.  
   
   
       88 . The method of  claim 86 , wherein, in the step of building the AI tool, at least one input tendency data is identified by considering the game playing ability of the mini automatic game engine and the difficulty information of the input tendency data, and the AI tool is built by using the identified input tendency data, in which the game playing style of the mini automatic game engine is divided into one of an attack type and a defense type according to any one of occupations, ages, and gender.  
   
   
       89 . The method of  claim 85 , further comprising the steps of: 
 receiving an upgrade request generated at a selected interval from the terminal receiving the AI tool; and    searching the AI tool from the database and providing the searched AI tool in response to the upgrade request to the terminal.    
   
   
       90 . The method of  claim 85 , further comprising the step of charging the player in case of providing the AI tool to the player.  
   
   
       91 . The method of  claim 81 , further comprising the steps of: 
 determining difficulty information or style information with respect to the generated input tendency data and storing the difficulty information or style information in association with the determined input tendency data for each game situation in a predetermined database;    classifying the input tendency data based on the difficulty information or the style information in the database;    building an AI tool by using the classified input tendency data;    storing each of the AI tool in association with the difficulty information or the style information in a second database;    searching the AI tool associated with the difficulty information or the style information from the second database; and    providing the searched AI tool to a terminal of the player in the case a request for the AI tool including the difficulty information or the style information from the terminal of the player.    
   
   
       92 . The method of  claim 91 , wherein the AI tool is installed in the terminal and controls a mini automatic game engine included in the terminal to play the game, and the mini automatic game engine determines one input tendency data associated with the game situation played by the mini automatic game engine from the input tendency data included in the AI tool and plays the game based on the determined input tendency data.  
   
   
       93 . The method of  claim 92 , wherein, in the step of building the AI tool, at least one input tendency data is identified by considering the game playing ability of the mini automatic game engine and the difficulty information of the input tendency data, and the AI tool is built by using the identified input tendency data, in which the game playing ability of the mini automatic game engine is divided into a high-skilled player, a middle-skilled player, and a low-skilled player.  
   
   
       94 . The method of  claim 92 , wherein, in the step of building the AI tool, at least one input tendency data is identified by considering the game playing ability of the mini automatic game engine and the difficulty information of the input tendency data, and the AI tool is built by using the identified input tendency data, in which the game playing style of the mini automatic game engine is divided into one of an attack type and a defense type according to any one of occupations, ages, and gender.  
   
   
       95 . The method of  claim 91 , further comprising the steps of: 
 receiving an upgrade request generated at a selected interval from the terminal receiving the AI tool; and    searching the AI tool from the database and providing the searched AI tool in response to the upgrade request to the terminal.    
   
   
       96 . The method of  claim 91 , further comprising the step of charging the player in case of providing the AI tool to the player.  
   
   
       97 . A method of instructing a game player, comprising the steps of: 
 allowing a game player to install an automatic game engine for instruction in game terminal; and    providing an optimized input of a player in the instruction mode via an interface by utilizing the automatic game engine for instruction.    
   
   
       98 . The method of  claim 97 , wherein the automatic game engine for instruction analyzes each game situation, has the optimized input information for each game situation for basic game playing, and provides the optimized input information to the player according to the analyzed game situation.  
   
   
       99 . The method of  claim 98 , wherein the optimized input information includes input information with respect to each game having at least two difficulties, which are different from each other.  
   
   
       100 . The method of  claim 99 , wherein, in providing the optimized input information, each of the analyzed game situations and a cause of the optimized input information according to the game situation are provided to the player.  
   
   
       101 . The method of  claim 97 , further comprising the step of acquiring an optimized input for each game situation of the game player while playing a game via the game terminal.  
   
   
       102 . A method of instructing a player in a card game, comprising the steps of: 
 generating an automatic game engine for instruction in card game in the case a request of playing a game for instruction in card game is received from a player of a card game terminal unit;    analyzing a group of cards of the player and opponent players by using the card instruction automatic game engine while the card instruction game is played and providing an expected genealogy and an expected genealogy probability of the player and the opponent players to the card game terminal unit; and    providing a desirable betting activity of the player to the card game terminal unit by using the card instruction automatic game engine according to the card analysis result.    
   
   
       103 . The method of  claim 102 , wherein the opponent player is formed of at least one automatic game engine in which the automatic game engine analyzes each card game situation, has input information for each analyzed card game situation, and automatically plays a game based on the input information.  
   
   
       104 . The method of  claim 103 , wherein the card instruction automatic game engine has input information optimized for each game situation in order to play a basic game, analyzes each card game situation, and provides the input information to the card game terminal unit according to the analyzed card game situation.  
   
   
       105 . The method of  claim 104 , wherein the expected genealogy and the expected genealogy probability are provided being computed in the direction of high in the case the game for instruction in card game is high type game, in the direction of low in the case the game for instruction in card game is low type game, and in both directions of high and low in the case the game for instruction in card game is a high-low selection type game.  
   
   
       106 . The method of  claim 104 , in the case the game for instruction in card game is one of a seven-card stud game and a seven-card stud high-low game in which it is required to select a card to be opened, further comprising the step of providing a group of cards to be opened by the card game terminal unit to the card game terminal unit based on the input information optimized for each game situation of the received card.  
   
   
       107 . The method of  claim 104 , in the case the game for instruction in card game is a high-low selection type game, further comprising the step of providing a direction including a highest expected genealogy probability from expected genealogy probabilities computed in the high direction and the low direction as an expected game direction when the game for instruction in card game is finished, and in the case two expected genealogy probabilities having highest probability in the high direction and the low direction have a value within previously set range, providing a swing to the card game terminal unit as the expected game direction.  
   
   
       108 . A method of playing a card game via a replicated player, comprising the steps of: 
 sounding out the intention of joining a card game played via a game terminal equipped with an automatic game engine in which the card game tendency of a player is replicated;    selecting that the player himself plays a card game or the automatic game engine plays a game by proxy in the case it is allowed to join the game; and    playing the card game by the selected player.    
   
   
       109 . The method of  claim 108 , wherein the automatic game engine computes input for each game situation and probability information of the input by monitoring card game play of the player more than a predetermined times and performs the input based on the probability information in the same game situation in the case the card game is played by proxy.  
   
   
       110 . A game apparatus using a replicated player, comprising: 
 a game access module for inquiring of a player whether the player will participate in a game via a game terminal equipped with an automatic game engine replicating the input tendency of the player;    a player selection module for selecting at least one of the player and the automatic game engine as a player to play the game in the case participating in the game is willingly allowed; and    a game playing module for playing the game by the selected player.    
   
   
       111 . A game apparatus having a function of instructing a game player, comprising: 
 a game program storage module for storing at least one game program;    a player interface module receiving a game selection command, a game play command, and an instruction mode playing command provided by a game player and displaying a game program corresponding to the received game selection command from the storage module;    a game play module interactively playing the game program selected by the received game play command via the player interface module; and    a game information supply module providing optimized input of the player for each game situation, the optimized input of the player playing the selected game via the game play module by the received instruction mode playing command received from the player interface module for each game situation.    
   
   
       112 . A system for instructing a game player, comprising: 
 a terminal of a player for request of playing a game for instruction;    an automatic game engine having input information optimized for each game situation for basic game play, analyzing each card game situation in the case the request of playing the game for instruction is received, and providing the input information optimized for the analyzed each card game situation to the terminal;    a game engine for controlling the operation of the automatic game engine for instruction and providing needed modules and game situations required in playing the game for instruction; and    database unit for storing information on a plurality of players and game information and providing the information to the automatic game engine for replication.    
   
   
       113 . A system of replicating a card player, comprising: 
 a terminal of a player for a request of replicating a player or playing a game by proxy;    a replication automatic game engine replicating the card group analysis tendency or betting tendency of the player by monitoring the player playing a card game in the case the request of replication the player is received and playing the game for the player in the case the request of playing a game by proxy is received;    a game engine controlling the generation and game playing by proxy of the replication automatic game engine and providing all sorts of required modules and game environments; and a database unit storing information on a plurality of players and card game and providing the information to the replication automatic game engine.    
   
   
       114 . The system of  claim 113 , wherein the replication automatic game engine comprises: 
 a replication initialization module setting an initial value of a replication database storing all sorts of information used by the replication automatic game engine;    a player tendency replication module replicating the game tendency of the player and storing the game tendency input data in the replication database; and    a game play proxy module searching the game tendency input data from the replication database and playing a card game by proxy based on the game tendency input data.    
   
   
       115 . The system of  claim 113 , wherein the game engine comprises a team play module supporting a team play function such that players form a team and play the card game.  
   
   
       116 . The system of  claim 113 , wherein the team play comprises a part or the whole of: 
 a team play of a player team including at least two players and a mixed player-replication automatic game engine team including at least one player and at least one replication automatic game engine module;    a team play of the player team and a replication automatic game engine team including at least two replication automatic game engine modules;    a team play of the player team and a mixed player-player replication automatic game engine team including at least one player and at least one replication automatic game engine in which the game tendency of the player is replicated; and    a team play of the mixed player-player replication automatic game engine team and the mixed player-player replication automatic game engine team.    
   
   
       117 . A system for instructing a card player, comprising: 
 a card game terminal unit of a player, for performing a request of playing a game for instructing a card game;    an automatic game engine for instruction having input information optimized for each game situation for basic game play, analyzing each card game situation in the case the request of playing the game for instructing a card game is received, and providing the input information optimized for the analyzed each card game situation to the card game terminal unit;    a game engine for controlling the operation of the instruction automatic game engine and providing all sorts of modules and game environments required in playing the game for instruction in card game; and    a database unit storing information on a plurality of players and card games and providing the information to the instruction automatic game engine.    
   
   
       118 . The system of  claim 117 , wherein the game engine provides a function of generating a card game instruction room formed of an automatic game engine module analyzing at least one game situation, having probability information with respect to input for each analyzed game situation, and automatically playing a game and an instruction automatic game engine module for playing a game for instructing the player in a card game.  
   
   
       119 . The system of  claim 118 , wherein the automatic game engine module comprises: 
 a card group analysis service module analyzing a group of cards of the player and opponent players while playing the game for instruction in card game and providing an expected genealogy and the probability of the expected genealogy of the player and the opponent players to the card game terminal unit;    a betting activity service module providing a betting activity optimized for each game situation by using analysis information of the group of open cards or betting order; and    a game information display module displaying information required in playing a card game, including the expected genealogy, the probability of the expected genealogy, and the betting activity.    
   
   
       120 . The system of  claim 119 , wherein the instruction automatic game engine module, in the case the game for instruction in card game is a seven-card stud game or a seven-card stud high-low game, further comprises an open card service module providing a group of cards to be opened by the card game terminal unit to the card game terminal unit based on the input information optimized for each game situation of received cards.  
   
   
       121 . The system in wired/wireless Internet environment of  claim 119 , wherein the instruction automatic game engine module, in the case the game for instruction in card game based on the automatic game engine is a high-low selection type game, further comprises a direction service module providing a direction including a highest expected genealogy probability from expected genealogy probabilities computed in the high direction and the low direction as an expected game direction when the game for instruction in card game is finished, and in the case two expected genealogy probabilities having highest probability in the high direction and the low direction have a value within previously set range, providing a swing to the card game terminal unit as the expected game direction.