84 search results - page 3 / 17 » Integrating Reinforcement Learning, Bidding and Genetic Algo... |
GECCO
2006
Springer
13 years 10 months ago
2006
Springer
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
ICAI
2004
13 years 8 months ago
2004
An explicit exploration strategy is necessary in reinforcement learning (RL) to balance the need to reduce the uncertainty associated with the expected outcome of an action and the...
ICRA
2010
IEEE
13 years 5 months ago
2010
IEEE
— Reinforcement learning (RL) is one of the most general approaches to learning control. Its applicability to complex motor systems, however, has been largely impossible so far d...
ICML
2007
IEEE
14 years 7 months ago
2007
IEEE
Many robot control problems of practical importance, including operational space control, can be reformulated as immediate reward reinforcement learning problems. However, few of ...
ICML
2006
IEEE
14 years 7 months ago
2006
IEEE
Recent decision-theoric planning algorithms are able to find optimal solutions in large problems, using Factored Markov Decision Processes (fmdps). However, these algorithms need ...