Sciweavers

Share
AAAI
1994

Learning Explanation-Based Search Control Rules for Partial Order Planning

10 years 5 months ago
Learning Explanation-Based Search Control Rules for Partial Order Planning
This paper presents snlp+ebl, the first implementation of explanation based learning techniques for a partial order planner. We describe the basic learning framework of snlp+ebl, including regression, explanation propagation and rule generation. We then concentrate on snlp+ebl's ability to learn from failures and present a novel approach that uses stronger domain and planner specific consistency checks to detect, explain and learn from the failures of plansat depthlimits. We will end with an empirical evaluation of the efficacy of this approach in improving planning performance.
Suresh Katukam, Subbarao Kambhampati
Added 02 Nov 2010
Updated 02 Nov 2010
Type Conference
Year 1994
Where AAAI
Authors Suresh Katukam, Subbarao Kambhampati
Comments (0)
books