Solving Graph Optimization Problems in a Framework for Monte-Carlo Search

Authors

  • Stefan Edelkamp Universität Bremen
  • Eike Externest Universität Bremen
  • Sebastian Kühl Universität Bremen
  • Sabine Kuske Universität Bremen

DOI:

https://doi.org/10.1609/socs.v8i1.18419

Abstract

In this paper we solve fundamental graph optimization problems like Maximum Clique and Minimum Coloring with recent advances of Monte-Carlo Search. The optimization problems are implemented as single-agent games in a generic state-space search framework, roughly comparable to what is encoded in PDDL for an action planner.

Socs 2017 Proceedings Cover

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Published

2021-09-01

How to Cite

Edelkamp, S., Externest, E., Kühl, S., & Kuske, S. (2021). Solving Graph Optimization Problems in a Framework for Monte-Carlo Search. Proceedings of the International Symposium on Combinatorial Search, 8(1), 163-164. https://doi.org/10.1609/socs.v8i1.18419

Issue

Vol. 8 No. 1 (2017): Tenth Annual Symposium on Combinatorial Search

Section

Extended Abstracts