Adaptive Planning for Markov Decision Processes with Uncertain Transition Models via Incremental Feature Dependency Discovery

Adaptive Planning for Markov Decision Processes with Uncertain Transition Models via Incremental Feature Dependency Discovery

Solving large scale sequential decision making problems without prior knowledge of the state transition model is a key problem in the planning literature. One approach to tackle this problem is to learn the state transition model online using limited observed measurements. We present an adaptive fun...

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Bibliographic Details
Main Authors:	Geramifard, Alborz, Chowdhary, Girish, How, Jonathan P., Ure, Nazim Kemal
Other Authors:	Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Format:	Article
Language:	en_US
Published:	Springer-Verlag 2013
Online Access:	http://hdl.handle.net/1721.1/81767 https://orcid.org/0000-0002-2508-1957 https://orcid.org/0000-0001-8576-1930

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