Extending Specialized Systems to a Generic Approach of Game Playing
Keywords:
General Game Playing, Specialized Systems, Game Bot, Reinforcement Learning, Classification of Games, OpenAI, Generic game Player, Game Description LanguageAbstract
Better decision making requires better analysis of the situation at hand. A program which can analyze the current situation better, can take better decisions, thus, increasing the likelihood of winning more games. Specialized game players are very narrow. They might outperform humans in a particular game and know nothing about any other game. They do only part of the work. Most of the definition, analysis and design is done in backend, within the systems by their programmers. Generic Game Bot are systems which are able to accept descriptions of any game at runtime and can use such definitions to play that game effectively, without any human intervention or supervision, i.e., they do not know the rules of the games beforehand. Generic Bot as such should be capable of playing simple games (like Snake) and complex games (like Chess), games in static or dynamic environments, games with complete and partial information, games with different numbers of players, with simultaneous or alternating turn of play, with or without communication among the players, and so forth.
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