- author = "Denis Robilliard and Cyril Fonlupt",
- title = "Towards Human-Competitive Game Playing for Complex Board Games with Genetic Programming",
- booktitle = "Artificial Evolution",
- year = "2015",
- editor = "Stephane Bonnevay and Pierrick Legrand and Nicolas Monmarche and Evelyne Lutton and Marc Schoenauer",
- volume = "9554",
- series = "LNCS",
- pages = "123--135",
- address = "Lyon, France",
- month = "26-28 " # oct,
- organisation = "Association Evolution Artificielle",
- publisher = "Springer",
- keywords = "genetic algorithms, genetic programming, MCTS",
- isbn13 = "978-3-319-31471-6",
-
URL = "
http://www-lisic.univ-littoral.fr/publis/1445328959.pdf",
-
DOI = "
10.1007/978-3-319-31471-6_10",
- size = "12 pages",
- 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.",
-
notes = "Published 2016
https://ea2015.inria.fr/ http://www.lifl.fr/EA/",
