Learning to Anticipate and Avoid Planning Problems through the Explanation of Failures

Kristian J. Hammond*

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

30 Scopus citations

Abstract

This paper presents an approach to learning during planning that focuses on learning to predict planning problems through an analysis of the planner's own failures. The need to predict failures in order to avoid them is argued and a method for leaming the features that predict problems from a causal analysis of planning failures is discussed. A further argument is also given concerning the natural integration of this approach to learning with an overall theory of case-based planning. An implementation of these learning ideas is presented in the case-based planner CHEF, which creates new plans from old in the domain of Szechwan cooking. The CHEF planner uses an anticipafe and avoid approach to planning problems that is sharply contrasted with the create and debug approach taken by existing planners.

Original languageEnglish (US)
Pages556-560
Number of pages5
StatePublished - 1986
Event5th National Conference on Artificial Intelligence, AAAI 1986 - Philadelphia, United States
Duration: Aug 11 1986Aug 15 1986

Conference

Conference5th National Conference on Artificial Intelligence, AAAI 1986
Country/TerritoryUnited States
CityPhiladelphia
Period8/11/868/15/86

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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