Mastering board games

From the earliest days of the computer era, games have been considered important vehicles for research in artificial intelligence (AI) (1). Game environments simplify many aspects of real-world problems yet retain sufficient complexity to challenge humans and machines alike. Most programs for playing classic board games have been largely human-engineered (2, 3). Sophisticated search methods, complex evaluation functions, and a variety of game-specific tricks have allowed programs to surpass the best human players. More recently, a learning approach achieved superhuman performance in the hardest of the classic games, Go (4), but was specific for this game and took advantage of human-derived game–specific knowledge.