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ECML
2004
Springer

Model Approximation for HEXQ Hierarchical Reinforcement Learning

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Model Approximation for HEXQ Hierarchical Reinforcement Learning
HEXQ is a reinforcement learning algorithm that discovers hierarchical structure automatically. The generated task hierarchy repthe problem at different levels of abstraction. In this paper we extend HEXQ with heuristics that automatically approximate the structure of the task hierarchy. Construction, learning and execution time, as well as storage requirements of a task hierarchy may be significantly reduced and traded off against solution quality.
Bernhard Hengst
Added 01 Jul 2010
Updated 01 Jul 2010
Type Conference
Year 2004
Where ECML
Authors Bernhard Hengst
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