Failure driven dynamic search control for partial order planners: an explanation based approach

摘要

Given the intractability of domain independent planning, the ability to control the search of a planner is vitally important. One way of doing this involves learning from search failures. This paper describes SNLP + EBL, the first implementation of an explanation based search control rule learning framework for a partial order (plan-space) planner. We will start by describing the basic learning framework of SNLP + EBL. We will then concentrate on SNLP + EBL's ability to learn from failures, and describe the results of empirical studies which demonstrate the effectiveness of the search control rules SNLP + EBL learns using our method.