50 search results - page 5 / 10 » Reinforcement Learning for Penalty Avoidance in Continuous S... |
MICAI
2009
Springer
14 years 1 months ago
2009
Springer
Reinforcement Learning is a commonly used technique in robotics, however, traditional algorithms are unable to handle large amounts of data coming from the robot’s sensors, requi...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
For a Markov Decision Process with finite state (size S) and action spaces (size A per state), we propose a new algorithm--Delayed Q-Learning. We prove it is PAC, achieving near o...
NIPS
2003
13 years 8 months ago
2003
We exploit some useful properties of Gaussian process (GP) regression models for reinforcement learning in continuous state spaces and discrete time. We demonstrate how the GP mod...
ROBOCUP
2000
Springer
13 years 11 months ago
2000
Springer
Q-learning, a most widely used reinforcement learning method, normally needs well-defined quantized state and action spaces to converge. This makes it difficult to be applied to re...
AROBOTS
1999
13 years 7 months ago
1999
We use reinforcement learning (RL) to compute strategies for multiagent soccer teams. RL may pro t signi cantly from world models (WMs) estimating state transition probabilities an...