Asynchronous stochastic approximation and Q-learning
John N. Tsitsiklis · 2002
Provides some general results on the convergence of a class of stochastic approximation algorithms and their parallel and asynchronous variants. The author then uses these results to study the Q-learning algorithm, a reinforcement learning method for solving Markov decision problems, and establishes its convergence under conditions more general than previously available.>