38 search results - page 5 / 8 » Improving reinforcement learning function approximators via ... |
NIPS
1994
13 years 7 months ago
1994
It is widely accepted that the use of more compact representations than lookup tables is crucial to scaling reinforcement learning (RL) algorithms to real-world problems. Unfortun...
PKDD
2010
Springer
13 years 3 months ago
2010
Springer
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
GECCO
2006
Springer
13 years 9 months ago
2006
Springer
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
ILP
2003
Springer
13 years 11 months ago
2003
Springer
RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
ECML
2004
Springer
13 years 11 months ago
2004
Springer
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....