449 search results - page 19 / 90 » Finding Structure in Reinforcement Learning |
136
Voted
CORR
2010
Springer
15 years 2 months ago
2010
Springer
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
135
Voted
IJCNN
2006
IEEE
15 years 9 months ago
2006
IEEE
— Biped robots based on the concept of (passive) dynamic walking are far simpler than the traditional fullycontrolled walking robots, while achieving a more natural gait and cons...
129
Voted
AAAI
2010
15 years 5 months ago
2010
Recent advancements in model-based reinforcement learning have shown that the dynamics of many structured domains (e.g. DBNs) can be learned with tractable sample complexity, desp...
126
Voted
ICML
2003
IEEE
15 years 8 months ago
2003
IEEE
Shaping can be an effective method for improving the learning rate in reinforcement systems. Previously, shaping has been heuristically motivated and implemented. We provide a for...
117
Voted
FUZZIEEE
2007
IEEE
15 years 10 months ago
2007
IEEE
— Reinforcement learning (RL) is a learning control paradigm that provides well-understood algorithms with good convergence and consistency properties. Unfortunately, these algor...