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» Learning Partially Observable Deterministic Action Models
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JAIR
2008
148views more  JAIR 2008»
13 years 9 months ago
Learning Partially Observable Deterministic Action Models
We present exact algorithms for identifying deterministic-actions' effects and preconditions in dynamic partially observable domains. They apply when one does not know the ac...
Eyal Amir, Allen Chang
AAAI
2006
13 years 10 months ago
Learning Partially Observable Action Models: Efficient Algorithms
We present tractable, exact algorithms for learning actions' effects and preconditions in partially observable domains. Our algorithms maintain a propositional logical repres...
Dafna Shahaf, Allen Chang, Eyal Amir
ICONIP
2009
13 years 7 months ago
Quasi-Deterministic Partially Observable Markov Decision Processes
We study a subclass of POMDPs, called quasi-deterministic POMDPs (QDET-POMDPs), characterized by deterministic actions and stochastic observations. While this framework does not mo...
Camille Besse, Brahim Chaib-draa
FORTE
2004
13 years 10 months ago
Symbolic Diagnosis of Partially Observable Concurrent Systems
Abstract. Monitoring large distributed concurrent systems is a challenging task. In this paper we formulate (model-based) diagnosis by means of hidden state history reconstruction,...
Thomas Chatain, Claude Jard
ECAI
2010
Springer
13 years 10 months ago
Learning action effects in partially observable domains
We investigate the problem of learning action effects in partially observable STRIPS planning domains. Our approach is based on a voted kernel perceptron learning model, where act...
Kira Mourão, Ronald P. A. Petrick, Mark Ste...