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HEXQ

HEXQ is a reinforcement learning algorithm created by Bernhard Hengst, which attempts to solve a Markov Decision Process by decomposing it… Expand
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Papers overview

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Review
2013
Review
2013
IONS FOR REINFORCEMENT LEARNING Abstraction is one of the most common ways of scaling up reinforcement learning, along with… Expand
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2011
2011
Hierarchical algorithms for Markov decision processes have been proved to be useful for the problem domains with multiple… Expand
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2007
2007
Scaling up reinforcement learning to large domains requires leveraging the structure in the domain. Hierarchical reinforcement… Expand
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2005
2005
HEXQ is a reinforcement learning algorithm that decomposes a problem into subtasks and constructs a hierarchy using state… Expand
2004
2004
HEXQ is a reinforcement learning algorithm that discovers hierarchical structure automatically. The generated task hierarchy… Expand
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2004
2004
Abstract Task hierarchies can be used to decompose an intractable problem into smaller more manageable tasks. This paper examines… Expand
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2004
2004
Task hierarchies can be used to decompose an intractable problem into smaller more manageable tasks. This paper explores how task… Expand
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2003
2003
This thesis addresses the open problem of automatically discovering hierarchical structure in reinforcement learning. Current… Expand
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Highly Cited
2002
Highly Cited
2002
An open problem in reinforcement learning is discovering hierarchical structure. HEXQ, an algorithm which automatically attempts… Expand
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