Machine learning and games

Abstract

The history of the interaction of machine learning and computer game-playing goes back to the earliest days of Artificial Intelligence, when Arthur Samuel worked on his famous checker-playing program, pioneering many machine-learning and game-playing techniques (Samuel, 1959, 1967). Since then, both fields have advanced considerably, and research in the intersection of the two can be found regularly in conferences in their respective fields and in general AI conferences. For surveys of the field we refer to Ginsberg (1998), Schaeffer (2000), Furnkranz (2001); edited volumes have been compiled by Schaeffer and van den Herik (2002) and by Furnkranz and Kubat (2001). In recent years, the computer games industry has discovered AI as a necessary ingredient to make games more entertaining and challenging and, vice versa, AI has discovered computer games as an interesting and rewarding application area. The industry’s perspective is witnessed by a plethora of recent books on gentle introductions to AI techniques for game programmers (Collins, 2002; Champanard, 2003; Bourg & Seemann, 2004; Schwab, 2004) or a series of edited collections of articles (Rabin, 2002, 2003, 2006). AI research on computer games began to follow developments in the games industry early on, but since John Laird’s keynote address at the AAAI 2000 conference, in which he advocated Interactive Computer Games as a challenging and rewarding application area for AI (Laird & van Lent, 2001), numerous workshops (Fu & Orkin, 2004; Aha et al., 2005), conferences, and special issues of journals (Forbus & Laird, 2002) demonstrate the growing importance of game-playing applications for Artificial Intelligence.