Lhtndt: Learn Htn Method Preconditions Using Decision Tree
ICINCO 2008: PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, VOL ICSO: INTELLIGENT CONTROL SYSTEMS AND OPTIMIZATION(2008)
摘要
In this paper, we describe LHTNDT, an algorithm that learns the preconditions of HTN methods by examining plan traces produced by another planner. LHTNDT extracts conditions for applying methods by using decision tree based algorithm. It considers the state of relevant domain objects in both current and goal states. Redundant training samples are removed using graph isomorphism. Our experiments, LHTNDT converged. It can learn most of preconditions correctly and quickly. 80% of our test problems were solved by preconditions extracted by 3/4 of plan traces needed for full convergence.
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关键词
AI planning, hierarchical task network planning, machine learning, decision tree, domain knowledge
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