1233 search results - page 114 / 247 » Reinforcement learning |
86
Voted
ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
We introduce new, efficient algorithms for value iteration with multiple reward functions and continuous state. We also give an algorithm for finding the set of all nondominated a...
112
Voted
NN
2006
Springer
15 years 22 days ago
2006
Springer
This review considers the theoretical problems facing agents that must learn and choose on the basis of reward or reinforcement that is uncertain or delayed, in implicit or proced...
112
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FLAIRS
2004
15 years 2 months ago
2004
er provides new techniques for abstracting the state space of a Markov Decision Process (MDP). These techniques extend one of the recent minimization models, known as -reduction, ...
81
Voted
ICML
2006
IEEE
16 years 1 months ago
2006
IEEE
When the transition probabilities and rewards of a Markov Decision Process are specified exactly, the problem can be solved without any interaction with the environment. When no s...
94
Voted
ICML
2000
IEEE
16 years 1 months ago
2000
IEEE
This paper discusses theoretical and experimental aspects of gradient-based approaches to the direct optimization of policy performance in controlled ??? ?s. We introduce ??? ?, a...