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LHTNDT: Learn HTN method preconditions using decision tree

Nargesian, F ; Sharif University of Technology | 2008

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  1. Type of Document: Article
  2. Publisher: 2008
  3. Abstract:
  4. 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
  5. Keywords:
  6. AI planning ; Domain knowledge ; Full convergence ; Graph isomorphism ; Hierarchical task networks ; Machine-learning ; Test problem ; Training sample ; Decision trees ; Learning systems ; Robotics ; Set theory ; Planning
  7. Source: ICINCO 2008 - 5th International Conference on Informatics in Control, Automation and Robotics, Funchal, Madeira, 11 May 2008 through 15 May 2008 ; Volume ICSO , January , 2008 , Pages 60-65 ; 9789898111319 (ISBN); 9789898111302 (ISBN)
  8. URL: https://www.scitepress.org/Papers/2008/14999/14999.pdf