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

Proceedings of the International Symposium on Combinatorial Search, 10

Volume

Vol. 10 No. 1 (2017): Tenth Annual Symposium on Combinatorial Search

Extended Abstracts

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.

10.1609/socs.v8i1.18419