1234 search results - page 60 / 247 » Multi-criteria Reinforcement Learning |
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ECML
2006
Springer
15 years 6 months ago
2006
Springer
In this article, I will consider Markov Decision Processes with two criteria, each defined as the expected value of an infinite horizon cumulative return. The second criterion is e...
126
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ECML
2004
Springer
15 years 9 months ago
2004
Springer
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
139
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KCAP
2009
ACM
15 years 10 months ago
2009
ACM
As computational learning agents move into domains that incur real costs (e.g., autonomous driving or financial investment), it will be necessary to learn good policies without n...
137
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COLT
1994
Springer
15 years 8 months ago
1994
Springer
Realistic domains for learning possess regularities that make it possible to generalize experience across related states. This paper explores an environment-modeling framework tha...
125
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AAAI
1998
15 years 5 months ago
1998
Learning on real robots in an real, unaltered environment provides an extremely challenging problem. Many of the simplifying assumptions made in other areas of learning cannot be ...