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Towards Human-Competitive Game Playing for Complex Board Games with Genetic Programming

Abstract : Recent works have shown that Genetic Programming (GP) can be quite successful at evolving human-competitive strategies for games ranging from classic board games, such as chess, to action video games. However to our knowledge GP was never applied to modern complex board games, so-called eurogames, such as Settlers of Catan, i.e. board games that typically involve four characteristics: they are non zero-sum games, multiplayer, with hidden information and random elements. In this work we study how GP can evolve artificial players from low level attributes of a eurogame named " 7 Wonders " , that features all the characteristics of this category. We show that GP can evolve competitive artificial intelligence (AI) players against human-designed AI or against Monte Carlo Tree Search, a standard in automatic game playing.
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Denis Robilliard, Cyril Fonlupt. Towards Human-Competitive Game Playing for Complex Board Games with Genetic Programming. International Conference on Artificial Evolution (Evolution Artificielle), EA 2015, Oct 2015, Lyon, France. pp.123 - 135, ⟨10.1007/978-3-319-31471-6_10⟩. ⟨hal-01488191⟩



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