Sciweavers

Share
KR
2004
Springer

Learning Probabilistic Relational Planning Rules

9 years 2 months ago
Learning Probabilistic Relational Planning Rules
To learn to behave in highly complex domains, agents must represent and learn compact models of the world dynamics. In this paper, we present an algorithm for learning probabilistic STRIPS-like planning operators from examples. We demonstrate the effective learning of rule-based operators for a wide range of traditional planning domains.
Hanna Pasula, Luke S. Zettlemoyer, Leslie Pack Kae
Added 02 Jul 2010
Updated 02 Jul 2010
Type Conference
Year 2004
Where KR
Authors Hanna Pasula, Luke S. Zettlemoyer, Leslie Pack Kaelbling
Comments (0)
books