| Authors |
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| Publication date |
2013
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| Host editors |
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| Book title |
Proceedings, The Tenth Symposium on Abstraction, Reformulation, and Approximation (SARA 2013)
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| ISBN |
|
| Event |
Symposium on Abstraction, Reformulation, and Approximation; 10 (Leavenworth, Wash.): 2013.07.11-12
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| Pages (from-to) |
123-127
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| Publisher |
Palo Alto, California: AAAI Press
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| Organisations |
-
Faculty of Science (FNWI) - Informatics Institute (IVI)
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| Abstract |
This paper introduces a novel approach for abstraction selection in reinforcement learning problems modelled as factored Markov decision processes (MDPs), for which a state is described via a set of state components. In abstraction selection, an agent must choose an abstraction from a set of candidate abstractions, each build up from a different combination of state components.
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| Document type |
Conference contribution
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| Note |
Extended abstract
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| Language |
English
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| Published at |
http://www.aaai.org/ocs/index.php/SARA/SARA13/paper/view/7259/6271
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