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Abstract: This paper introduces an integration of reinforcement learning and behavior-based control designed to produce real-time learning in situated agents. The model layers a distributed and asynchronous reinforcement learning algorithm over a learned topological map and standard behavioral substrate to create a reinforcement learning complex. The topological map creates a small and task-relevant state space that aims to make learning feasible, while the distributed and asynchronous aspects of the... (Update)
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BibTeX entry: (Update)
G.D. Konidaris and G.M. Hayes. An Architecture for Behavior-Based Reinforcement Learning. To appear, Adaptive Behavior, 2004. http://citeseer.ist.psu.edu/konidaris05architecture.html More
@article(konidaris05architecture, title = "An Architecture for Behavior-Based Reinforcement Learning", author = "G.D. Konidaris and G.M. Hayes", journal = "Adaptive Behavior", volume = 13, number = 1, year = 2005, pages = "5---32" )Citations (may not include all citations):
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