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- W3217142014 abstract "Games and Artificial Intelligence (AI) have had a tight relationship for many years. A multitude of games have been used as environments in which AI players can learn to act and interact with others or the game mechanics directly; used as optimisation problems; used as generators of large amounts of data which can be analysed to learn about the game, or about the players; or used as containers of content which can be automatically generated by AI methods. Yet many of these environments have been very simple and limited in scope. We propose here a much more complex environment based on the boardgame Terraforming Mars, implemented as part of the Tabletop Games Framework: a very large and dynamic action space, hidden information, large amounts of content, resource management and high variability make this problem domain stand out in the current landscape and a very interesting problem for AI methods of multiple domains. We include results of baseline AI game-players in this game and in-depth analysis of the game itself, together with an exploration of problem complexity, challenges and opportunities." @default.
- W3217142014 created "2021-12-06" @default.
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- W3217142014 date "2021-10-04" @default.
- W3217142014 modified "2023-10-16" @default.
- W3217142014 title "TAG: Terraforming Mars" @default.
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