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general game playing

nounAlso: GGP, Game Description Language, GDL

In plain wordsBuilding AI players that are handed the rules of a game they have never seen and must work out how to play it well on their own, with no game-specific help from their programmers.

  1. The research problem of building AI systems that receive the rules of a game they have never encountered, as a formal description, only when play begins, so that no knowledge specific to that game can be programmed in. In the Stanford framework, rules are written in the Game Description Language (GDL), a DatalogDatalog, prop. n.: A small logic language for asking questions of a database with rules, including rules that refer to themselves, such as 'X is an ancestor of Y if X is a parent of an ancestor of Y'.-like logic language specifying players, initial state, legal moves, state updates, termination and payoffs; extensions cover chance and hidden information. Players must analyze the rules, construct evaluation strategies on the fly and search, and the most successful competitors adopted Monte Carlo tree searchMonte Carlo tree search, n.: A way for a game-playing program to choose a move by simulating many possible continuations, focusing on the most promising lines, and picking the move that worked out best on average., which needs no hand-built evaluation functionevaluation function, n.: In a game-playing program, a formula that looks at a board position and gives it a score saying how good it is, without playing the game out to the end.. The field anticipated the generality later pursued by AlphaZeroAlphaZero, prop. n.: A 2017 DeepMind program that taught itself chess, shogi and Go from nothing but the rules by playing against itself, and within hours of training beat the strongest existing programs., which learns any perfect-information game from its rules by self-playself-play, n.: Training an AI by having it play against copies of itself, so it always has an opponent at its own level and can keep improving without human examples., and by benchmarks that test language modelslarge language model, n.: A computer program trained on enormous amounts of text to predict the words that come next. At vast scale, that simple skill lets it chat, answer questions, translate, summarize and write code. on novel games.

Origin

Barney Pell's Metagame (1992) explored programs that play whole classes of chess-like games. Michael Genesereth's Stanford Logic Group defined GDL and launched the annual AAAI General Game Playing Competition in 2005.

Related

See also
  • Monte Carlo tree searchMonte Carlo tree search, n.: A way for a game-playing program to choose a move by simulating many possible continuations, focusing on the most promising lines, and picking the move that worked out best on average.
  • game treegame tree, n.: A branching diagram of every way a game could unfold: each point is a position, each branch a possible move, and the tips of the branches are wins, losses or draws.
  • AlphaZeroAlphaZero, prop. n.: A 2017 DeepMind program that taught itself chess, shogi and Go from nothing but the rules by playing against itself, and within hours of training beat the strongest existing programs.
  • evaluation functionevaluation function, n.: In a game-playing program, a formula that looks at a board position and gives it a score saying how good it is, without playing the game out to the end.
  • DatalogDatalog, prop. n.: A small logic language for asking questions of a database with rules, including rules that refer to themselves, such as 'X is an ancestor of Y if X is a parent of an ancestor of Y'.
  • artificial general intelligenceartificial general intelligence, n.: AI that could learn and do almost any mental task a capable adult can, rather than excelling at one narrow job. Experts disagree on the exact bar and on when, or whether, it will arrive.

Sources

  1. Genesereth, M., Love, N. & Pell, B. (2005). General Game Playing: Overview of the AAAI Competition. AI Magazine 26(2), 62–72.