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Hi, > My task is to create the AI-based computer player (bot, agent - sound too > high ;)) for the game whose rules you may find at > http://www.brettspielwelt.de/en/Hilfe/Anleitungen/Fuersten/index.html. I > believe this webpage specifies the rules clearly. > > The production staff suggested me to use some evolutionary solutions. I am > now looking for the best idea. As the game is somewhat linear, I think its > course may be described as a sequence of data that forms up a GA chromosome. > Like in the case of http://satirist.org/learn-game/methods/ga/chess.html, I > may set up a hundred of players (specimens) that would play with each other > (in pairs, threes..?), starting with random actions (of course constrained > by the rules). After each game, fitness may probably be calculated > proportionally to the prestige points gained by the player. > > Do you think it's a good way to go? :)) > Well, I didn't read the rules in details, but I think you must be careful in what you put in your chromosome. You should not put a sequence of actions, because the value of an action depends on the state of the game (the other players' actions). Thus, there is probably no "optimal" sequence of action (and if there is, the game must be pretty boring). Moreover, if you end up with what you think is a "good" AI player described by the winning genome, this player would always play the same actions again and again - pretty boring again. If you want to go the evolutionary way, a gene in your chromosome would need to code the action to take in a given situation. The problem is to find a good way to describe a situation. I have no magic solution for you here. I think that the easiest way for you to get a decent AI player would be to use a basic rule-based system, fed by the knowledge of good human players. It's probably not very exciting, but it should give you a working solution faster than the more exotic AI stuff. Well, just my 2 cents, I have no real experience in this kind of game, so feel free to correct me ;) Olivier
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