A New Efficient In Situ Sampling Model for Heuristic Selection in Optimal Search

  • Santiago Franco
  • Michael W. Barley
  • Patricia J. Riddle
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8272)


Techniques exist that enable problem-solvers to automatically generate an almost unlimited number of heuristics for any given problem. Since they are generated for a specific problem, the cost of selecting a heuristic must be included in the cost of solving the problem. This involves a tradeoff between the cost of selecting the heuristic and the benefits of using that specific heuristic over using a default heuristic. The question we investigate in this paper is how many heuristics can we handle when selecting from a large number of heuristics and still have the benefits outweigh the costs. The techniques we present in this paper allow our system to handle several million candidate heuristics.


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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Santiago Franco
    • 1
  • Michael W. Barley
    • 1
  • Patricia J. Riddle
    • 1
  1. 1.Department of Computer ScienceUniversity of AucklandNew Zealand

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