A Hierarchical Task-Network Planner Based on Symbolic Model Checking

Abstract

Although several approaches have been developed for planning in non-deterministic domains, solving large planning problems is still quite difficult. In this work, we present a novel algorithm, called YoYo, for planning in non- deterministic domains under the assumption of full observability. This algorithm enables us to combine the power of search-control strategies as in Planning with Hierarchical Task Networks (HTNs) with techniques from the Planning via Symbolic Model-Checking (SMC). Our experimental evaluation confirms the potentialities of our approach, demonstrating that it combines the advantages of these paradigms.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2005
Accession Number
ADA447974

Entities

People

  • Dana S. Nau
  • Marco Pistore
  • Paolo Traverso
  • Ugur Kuter

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Artificial Intelligence
  • Computations
  • Computer Science
  • Computers
  • Decomposition
  • Engineering
  • Explosions
  • Information Operations
  • Language
  • Mathematics
  • Models
  • Software Development
  • Test And Evaluation
  • Transitions
  • Universities

Fields of Study

  • Computer science

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Mathematical Modeling and Probability Theory.
  • Systems Analysis and Design