Multi-time models for temporally abstract planning

NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10, (1998): 1050-1056

Cited: 159|Views30
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Abstract

Planning and learning at multiple levels of temporal abstra ction is a key problem for artificial intelligence. In this paper we summar ize an ap- proach to this problem based on the mathematical framework of Markov decision processes and reinforcement learning. Current mo del-based re- inforcement learning is based on one-step models tha...More

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