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» Learning and reasoning about interruption
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UAI
2008
13 years 10 months ago
Model-Based Bayesian Reinforcement Learning in Large Structured Domains
Model-based Bayesian reinforcement learning has generated significant interest in the AI community as it provides an elegant solution to the optimal exploration-exploitation trade...
Stéphane Ross, Joelle Pineau
CONNECTION
2006
101views more  CONNECTION 2006»
13 years 8 months ago
Learning acceptable windows of contingency
By learning a range of possible times over which the effect of an action can take place, a robot can reason more effectively about causal and contingent relationships in the world...
Kevin Gold, Brian Scassellati
AIED
2009
Springer
14 years 3 months ago
Toward Scenario Adaptation for Learning
Abstract. This paper presents a methodology for automatically customizing a scenario to suit a learner’s abilities, needs, or goals. Training scenarios are often utilized to give...
James Niehaus, Mark Riedl
ACL
2012
11 years 11 months ago
Labeling Documents with Timestamps: Learning from their Time Expressions
Temporal reasoners for document understanding typically assume that a document’s creation date is known. Algorithms to ground relative time expressions and order events often re...
Nathanael Chambers
IAT
2008
IEEE
13 years 8 months ago
Structured Learning of Component Dependencies in AmI Systems
As information and communication technologies are becoming an integral part of our homes, the demand for AmI systems with assistive functionality is increasing. A great effort has...
Todor Dimitrov, Josef Pauli, Edwin Naroska, Christ...