43 search results - page 2 / 9 » The O.D.E. Method for Convergence of Stochastic Approximatio... |
COLT
2004
Springer
14 years 1 months ago
2004
Springer
Abstract. We consider Reinforcement Learning for average reward zerosum stochastic games. We present and analyze two algorithms. The first is based on relative Q-learning and the ...
ECML
2004
Springer
14 years 1 months ago
2004
Springer
Although tabular reinforcement learning (RL) methods have been proved to converge to an optimal policy, the combination of particular conventional reinforcement learning techniques...
WSC
2008
13 years 11 months ago
2008
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...
AI
2002
Springer
13 years 8 months ago
2002
Springer
Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on ...
ICML
2007
IEEE
14 years 9 months ago
2007
IEEE
Reinforcement learning algorithms can become unstable when combined with linear function approximation. Algorithms that minimize the mean-square Bellman error are guaranteed to co...