Abstract
Game playing is a major application area for research in artificial intelligence in general (Schaeffer and van den Herik 2002) and for machine learning in particular (Fürnkranz and Kubat 2001). Traditionally, the field is concerned with learning in strategy games such as tic-tac-toe (Michie 1963), checkers (Samuel’s checkers player), backgammon (TD-Gammon), chess (Baxter et al. 2000; Björnsson and Marsland 2003; Donninger and Lorenz 2006; Sadikov and Bratko 2006), Go (Silver et al. 2016), Othello (Buro 2002), poker (Billings et al. 2002), or bridge (Amit and Markovitch 2006). However, recently computer and video games have received increased attention (Laird and van Lent 2001; Spronck et al. 2006; Ponsen et al. 2006).
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Fürnkranz, J. (2017). Machine Learning and Game Playing. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_509
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DOI: https://doi.org/10.1007/978-1-4899-7687-1_509
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