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Predicting Optimal Solution Cost with Bidirectional Stratified Sampling (Abstract)

Conference Paper Extended Abstracts of Papers Presented Elsewhere Algorithms and Complexity · Artificial Intelligence · Automated Planning and Scheduling

Abstract

Optimal planning and heuristic search systems solve state-space searchproblems by finding a least-cost path from start to goal. As a byproduct of having an optimal path they also determine the optimal solution cost. In this paper we focus on the problem of determining the optimal solution cost for a state-space search problem directly, i. e. , without actually finding a solution path of that cost. We present an efficient algorithm, BiSS, based on ideas of bidirectional search and stratified sampling that produces accurate estimates of the optimal solution cost. Our method is guaranteed to return the optimal solution cost in the limit as the sample size goes to infinity.

Authors

Keywords

  • Optimal Solution Cost Prediction
  • SCP

Context

Venue
International Symposium on Combinatorial Search
Archive span
2010-2024
Indexed papers
598
Paper id
389613787945765882
v2026.09.13