Problem Difficulty and the Phase Transition in Heuristic Search

Authors

  • Eldan Cohen University of Toronto
  • J. Christopher Beck University of Toronto

DOI:

https://doi.org/10.1609/aaai.v31i1.10658

Keywords:

Heuristic search, Phase transition, Greedy Best First Search, GBFS, Problem Hardness

Abstract

In the recent years, there has been significant work on the difficulty of heuristic search problems, identifying different problem instance characteristics that can have a significant impact on search effort. Phase transitions in the solubility of random problem instances have proved useful in the study of problem difficulty for other classes of computational problems, notably SAT and CSP, and it has been shown that the hardest problems typically occur during this rapid transition. In this work, we perform the first empirical investigation of the phase transition phenomena for heuristic search. We establish the existence of a rapid transition in the solubility of an abstract model of heuristic search problems and show that, for greedy best first search, the hardest instances are associated with the phase transition region. We then perform a novel investigation of the behavior of heuristics of different strength across the solubility spectrum. Finally, we demonstrate that the behavior of our abstract model carries over to commonly used benchmark problems including the Pancake Problem, Grid Navigation, TopSpin, and the Towers of Hanoi. An interesting deviation is observed and explained in the Sliding Puzzle.

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Published

2017-02-12

How to Cite

Cohen, E., & Beck, J. C. (2017). Problem Difficulty and the Phase Transition in Heuristic Search. Proceedings of the AAAI Conference on Artificial Intelligence, 31(1). https://doi.org/10.1609/aaai.v31i1.10658

Issue

Section

AAAI Technical Track: Heuristic Search and Optimization