374 search results - page 28 / 75 » Multiagent Reinforcement Learning: Theoretical Framework and... |
ICML
2007
IEEE
14 years 8 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...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
Hierarchical reinforcement learning is a general framework which attempts to accelerate policy learning in large domains. On the other hand, policy gradient reinforcement learning...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
In the model-based policy search approach to reinforcement learning (RL), policies are found using a model (or "simulator") of the Markov decision process. However, for ...
ICONIP
2009
13 years 5 months ago
2009
Reinforcement learning induces non-stationarity at several levels. Adaptation to non-stationary environments is of course a desired feature of a fair RL algorithm. Yet, even if the...