UM Translog: A Planning Domain for the Development and Benchmarking of Planning Systems

Abstract

The last 20 years of Artificial Intelligence (AI) planning research has discovered a wide variety of planning techniques, such as state-space search, hierarchical planning, case-based planning, and reactive planning. These techniques have been implemented in numerous planning systems. Initially, a number of simple toy domains have been devised to assist in the analysis and evaluation of planning systems and techniques. The most well known examples are "Blocks World" and "Towers of Hanoi." As planning systems grow in sophistication and capabilities, however, there is a clear need for planning benchmarks with matching complexity to evaluate those new features and capabilities. UM Translog is a planning domain designed specifically for this purpose. UM Translog was inspired by the CMU Transport Logistics domain developed by Manuela Veloso. UM Translog is an order of magnitude larger in size (41 actions versus 6), number of features, and types of interactions. It provides a rich set of entities, attributes, actions, and conditions, which can be used to specify rather complex planning problems with a variety of plan interactions. The detailed set of operators provides long plans (40 steps) with many possible solutions to the same problem, and thus this domain can also be used to evaluate the solution quality of planning systems. The UM Translog domain has been used with the Universal Method-Composition Planner (UMCP), UM Nonlin, and CaPER planning systems thus far.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1995
Accession Number
ADA445809

Entities

People

  • Brian P. Kettler
  • James Hendler
  • Kutluhan Erol
  • Scott Andrews

Organizations

  • University of Maryland

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Artificial Intelligence
  • Computer Science
  • Computers
  • Information Operations
  • Maryland
  • Military Research
  • Universities

Readers

  • Artificial Intelligence
  • Computer Science.
  • Industrial Economics

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - DoD AI Strategy
  • AI & ML - Machine Learning Algorithms
  • Space
  • Space - Spacecraft Maneuvers