113 search results - page 2 / 23 » Learning Representation and Control in Continuous Markov Dec... |
SARA
2007
Springer
13 years 11 months ago
2007
Springer
Several recent techniques for solving Markov decision processes use dynamic Bayesian networks to compactly represent tasks. The dynamic Bayesian network representation may not be g...
UAI
2004
13 years 6 months ago
2004
We describe an approach for exploiting structure in Markov Decision Processes with continuous state variables. At each step of the dynamic programming, the state space is dynamica...
ICML
2006
IEEE
14 years 6 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 ...
ICML
1996
IEEE
13 years 9 months ago
1996
IEEE
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
EWRL
2008
13 years 7 months ago
2008
Abstract. We consider a control problem where the decision maker interacts with a standard Markov decision process with the exception that the reward functions vary arbitrarily ove...