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» Learning Partially Observable Action Schemas
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AAAI
2006
13 years 6 months ago
Learning Partially Observable Action Schemas
We present an algorithm that derives actions' effects and preconditions in partially observable, relational domains. Our algorithm has two unique features: an expressive rela...
Dafna Shahaf, Eyal Amir
AAAI
2007
13 years 6 months ago
A Robot That Uses Existing Vocabulary to Infer Non-Visual Word Meanings from Observation
The authors present TWIG, a visually grounded wordlearning system that uses its existing knowledge of vocabulary, grammar, and action schemas to help it learn the meanings of new ...
Kevin Gold, Brian Scassellati
AAAI
2006
13 years 6 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
JAIR
2008
148views more  JAIR 2008»
13 years 4 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
ECAI
2010
Springer
13 years 5 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...