Applying Anytime Heuristic Search to Cost-Optimal HTN Planning

  • Alexandre Menif
  • Christophe Guettier
  • Éric Jacopin
  • Tristan Cazenave
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 818)

Abstract

This paper presents a framework for cost-optimal Hierarchical Task Network (HTN) planning. The framework includes an optimal algorithm combining a branch-and-bound with a heuristic search, which can also be used as a near-optimal algorithm given a time limit. It also includes different heuristics based on weighted cost estimations and different decomposition strategies. The different elements from this framework are empirically evaluated on three planning domains, one of which is modeling a First-Person Shooter game.

The empirical results establish the superiority on some domains of a decomposition strategy that prioritizes the most abstract tasks. They also highlight that the best heuristic formulation for the three domains is computed from linear combinations of optimistic and pessimistic cost estimations.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Alexandre Menif
    • 3
  • Christophe Guettier
    • 1
  • Éric Jacopin
    • 2
  • Tristan Cazenave
    • 3
  1. 1.Safran Electronics & DefenseMassy CedexFrance
  2. 2.MACCLIA, CREC Saint Cyr, Écoles de CoëtquidanGuer CedexFrance
  3. 3.LAMSADEUniversité Paris-DauphineParisFrance

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