473 search results - page 3 / 95 » Optimal policy switching algorithms for reinforcement learni... |
ICANNGA
2007
Springer
13 years 11 months ago
2007
Springer
Reinforcement Learning (RL) is analyzed here as a tool for control system optimization. State and action spaces are assumed to be continuous. Time is assumed to be discrete, yet th...
AI
2002
Springer
13 years 5 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
2002
IEEE
14 years 6 months ago
2002
IEEE
Searching the space of policies directly for the optimal policy has been one popular method for solving partially observable reinforcement learning problems. Typically, with each ...
NIPS
2003
13 years 6 months ago
2003
Significant plasticity in sensory cortical representations can be driven in mature animals either by behavioural tasks that pair sensory stimuli with reinforcement, or by electro...
IJCAI
2001
13 years 6 months ago
2001
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...