200 search results - page 18 / 40 » Point-Based Policy Iteration |
MICAI
2009
Springer
14 years 2 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...
AI
2002
Springer
13 years 7 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 ...
ICMLA
2010
13 years 5 months ago
2010
Reinforcement learning algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, their traini...
NORDSEC
2009
Springer
14 years 2 months ago
2009
Springer
Runtime enforcement is a common mechanism for ensuring that program executions adhere to constraints specified by a security policy. It is based on two simple ideas: the enforceme...
GECCO
2004
Springer
14 years 1 months ago
2004
Springer
Abstract. Factored Markov Decision Processes is the theoretical framework underlying multi-step Learning Classifier Systems research. This framework is mostly used in the context ...