Section: Application Domains

Games

The problem of artificial intelligence in games consists in choosing actions of players in order to produce artificial opponents. Most games can be formalized as Markov decision problems, so they can be approached with reinforcement learning.

In particular, SequeL was a pioneer of Monte Carlo Tree Search, a technique that obtained spectacular successes in the game of Go. Other application domains include the game of poker and the Japanese card game of hanafuda.