651 search results - page 38 / 131 » Algorithms for Inverse Reinforcement Learning |
AI
2002
Springer
13 years 9 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 ...
PKDD
2009
Springer
14 years 3 months ago
2009
Springer
Abstract. Innovations such as optimistic exploration, function approximation, and hierarchical decomposition have helped scale reinforcement learning to more complex environments, ...
WSC
2008
13 years 11 months ago
2008
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...
PKDD
2009
Springer
14 years 3 months ago
2009
Springer
Abstract. The Factored Markov Decision Process (FMDP) framework is a standard representation for sequential decision problems under uncertainty where the state is represented as a ...
CIIA
2009
13 years 10 months ago
2009
Petroleum industry production systems are highly automatized. In this industry, all functions (e.g., planning, scheduling and maintenance) are automated and in order to remain comp...