For an introduction to reinforcement learning, see Szepesvári [2010], Sutton and Barto [1998], and Kaelbling et al. [1996]. Bertsekas and Tsitsiklis [1996] investigate function approximation and its interaction with reinforcement learning. Powell [2014] describes various applications of reinforcement learning to energy systems.

Mnih et al. [2015] describe how reinforcement learning combined with neural networks was used to solve classic Atari computer games, and Silver et al. [2016] show how learning can be used for the game of Go.

The learning of games and the WoLF strategy is based on PHC of Bowling and Veloso [2002]. Busoniu et al. [2008] survey multiagent reinforcement learning.