Monte-Carlo tree search for the physical travelling salesman problem

Authors:
Diego Perez;Philipp Rohlfshagen;Simon M. Lucas
Affiliations:
School of Computer Science and Electronic Engineering, University of Essex, Colchester, United Kingdom;School of Computer Science and Electronic Engineering, University of Essex, Colchester, United Kingdom;School of Computer Science and Electronic Engineering, University of Essex, Colchester, United Kingdom
Venue:
EvoApplications'12 Proceedings of the 2012t European conference on Applications of Evolutionary Computation
Year:
2012

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Abstract

The significant success of MCTS in recent years, particularly in the game Go, has led to the application of MCTS to numerous other domains. In an ongoing effort to better understand the performance of MCTS in open-ended real-time video games, we apply MCTS to the Physical Travelling Salesman Problem (PTSP). We discuss different approaches to tailor MCTS to this particular problem domain and subsequently identify and attempt to overcome some of the apparent shortcomings. Results show that suitable heuristics can boost the performance of MCTS significantly in this domain. However, visualisations of the search indicate that MCTS is currently seeking solutions in a rather greedy manner, and coercing it to balance short term and long term constraints for the PTSP remains an open problem.