Sequential Decision Making in Heuristic Search

  • Eyke Hüllermeier
Part of the International Centre for Mechanical Sciences book series (CISM, volume 472)


The order in which nodes are explored in a (depth-first) iterative deepening search strategy is principally determined by the condition under which a path of the search tree is cut off in each search phase. A corresponding criterion, which has a strong influence on the performance of the overall (heuristic) search procedure, is generally realized in the form of an upper cost bound. In this paper, we develop an effective and computationally efficient termination criterion based on statistical methods of change detection. The criterion is local in the sense that it depends on properties of a path itself, rather than on the comparison with other paths. Loosely speaking, the idea is to take a systematic change in the (heuristic) evaluation of nodes along a search path as an indication of suboptimality. An expected utility criterion which also takes the consequence of the suboptimal search decision on the solution quality into account is proposed as a generalization of this idea.


Change Detection Heuristic Search Nuisance Parameter Search Path Search Phase 
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 Wien 2003

Authors and Affiliations

  • Eyke Hüllermeier
    • 1
  1. 1.Department of Mathematics and InformaticsUniversity of MarburgGermany

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