250 search results - page 27 / 50 » Learning action effects in partially observable domains |
105
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CORR
2010
Springer
14 years 6 months ago
2010
Springer
This report outlines the use of a relational representation in a Multi-Agent domain to model the behaviour of the whole system. A desired property in this systems is the ability of...
ICML
2008
IEEE
15 years 10 months ago
2008
IEEE
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
AIPS
2006
14 years 11 months ago
2006
Planning for partially observable, nondeterministic domains is a very signi cant and computationally hard problem. Often, reasonable assumptions can be drawn over expected/nominal...
105
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AIIDE
2009
14 years 7 months ago
2009
This paper proposes an Integrated MDP and POMDP Learning AgeNT (IMPLANT) architecture for adaptation in modern games. The modern game world basically involves a human player actin...
123
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AAAI
2010
14 years 11 months ago
2010
Data sparsity is a major problem for collaborative filtering (CF) techniques in recommender systems, especially for new users and items. We observe that, while our target data are...