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» Goal-Based Decisions for Dynamic Planning
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AAAI
1996
14 years 11 months ago
Rewarding Behaviors
Markov decision processes (MDPs) are a very popular tool for decision theoretic planning (DTP), partly because of the welldeveloped, expressive theory that includes effective solu...
Fahiem Bacchus, Craig Boutilier, Adam J. Grove
VEE
2005
ACM
140views Virtualization» more  VEE 2005»
15 years 3 months ago
Planning for code buffer management in distributed virtual execution environments
Virtual execution environments have become increasingly useful in system implementation, with dynamic translation techniques being an important component for performance-critical ...
Shukang Zhou, Bruce R. Childers, Mary Lou Soffa
ICMLA
2009
14 years 7 months ago
Automatic Feature Selection for Model-Based Reinforcement Learning in Factored MDPs
Abstract--Feature selection is an important challenge in machine learning. Unfortunately, most methods for automating feature selection are designed for supervised learning tasks a...
Mark Kroon, Shimon Whiteson
ATAL
2004
Springer
15 years 3 months ago
Teaching and Working with Robots as a Collaboration
New applications for autonomous robots bring them into the human environment where they are to serve as helpful assistants to untrained users in the home or office, or work as ca...
Cynthia Breazeal, Guy Hoffman, Andrea Lockerd
ALDT
2009
Springer
142views Algorithms» more  ALDT 2009»
15 years 4 months ago
Finding Best k Policies
Abstract. An optimal probabilistic-planning algorithm solves a problem, usually modeled by a Markov decision process, by finding its optimal policy. In this paper, we study the k ...
Peng Dai, Judy Goldsmith