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» Approximation Algorithms for Partial Covering Problems
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ATAL
2009
Springer
14 years 11 days ago
Lossless clustering of histories in decentralized POMDPs
Decentralized partially observable Markov decision processes (Dec-POMDPs) constitute a generic and expressive framework for multiagent planning under uncertainty. However, plannin...
Frans A. Oliehoek, Shimon Whiteson, Matthijs T. J....
ECML
2005
Springer
13 years 11 months ago
Model-Based Online Learning of POMDPs
Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
Guy Shani, Ronen I. Brafman, Solomon Eyal Shimony
FLAIRS
2008
13 years 8 months ago
State Space Compression with Predictive Representations
Current studies have demonstrated that the representational power of predictive state representations (PSRs) is at least equal to the one of partially observable Markov decision p...
Abdeslam Boularias, Masoumeh T. Izadi, Brahim Chai...
GRAPHICSINTERFACE
2000
13 years 7 months ago
Animating Athletic Motion Planning By Example
Character animation is usually reserved for highly skilled animators and computer programmers because few of the available tools allow the novice or casual user to create compelli...
Ronald A. Metoyer, Jessica K. Hodgins
ATAL
2009
Springer
14 years 11 days ago
An empirical analysis of value function-based and policy search reinforcement learning
In several agent-oriented scenarios in the real world, an autonomous agent that is situated in an unknown environment must learn through a process of trial and error to take actio...
Shivaram Kalyanakrishnan, Peter Stone