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Flexible Planning Problems & Flexible Graphplan

  • Ian Miguel
Part of the Distinguished Dissertations book series (DISTDISS)

Abstract

This chapter argues that, just as in the case of classical CSP, the classical AI Planning framework is too rigid to capture the full subtlety of many real problems. This is due to the fact that it too is founded on hard constraints, and hence has no capability of making compromises. In order to address this issue, a new flexible planning problem is defined which is designed to allow a tradeoff between the length of a plan and the number of compromise decisions it contains.

Keywords

Planning Graph Satisfaction Degree Flexible Operator Domain Element Graph Expansion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London 2004

Authors and Affiliations

  • Ian Miguel
    • 1
  1. 1.University of YorkUSA

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