22 search results - page 3 / 5 » Tighter Value Function Bounds for Bayesian Reinforcement Lea... |
NIPS
2007
13 years 9 months ago
2007
Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...
NIPS
2001
13 years 8 months ago
2001
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
JMLR
2006
13 years 7 months ago
2006
In this article we describe a set of scalable techniques for learning the behavior of a group of agents in a collaborative multiagent setting. As a basis we use the framework of c...
AI
1998
Springer
13 years 7 months ago
1998
Springer
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
In this paper we consider the problem of policy evaluation in reinforcement learning, i.e., learning the value function of a fixed policy, using the least-squares temporal-differe...