Title :
The 2013 Multi-objective Physical Travelling Salesman Problem Competition
Author :
Perez, Diego ; Powley, Edward ; Whitehouse, Daniel ; Samothrakis, Spyridon ; Lucas, Simon ; Cowling, Peter I.
Author_Institution :
Sch. of Comput. Sci. & Electron. Eng., Univ. of Essex, Colchester, UK
Abstract :
This paper presents the game, framework, rules and results of the Multi-objective Physical Travelling Salesman Problem (MO-PTSP) Competition, that was held at the 2013 IEEE Conference on Computational Intelligence in Games (CIG). The MO-PTSP is a real-time game that can be seen as a modification of the Travelling Salesman Problem, where the player controls a ship that must visit a series of waypoints in a maze while minimizing three opposing goals: time spent, fuel consumed and damage taken. The rankings of the competition are computed using multi-objective concepts, a novel approach in the field of game artificial intelligence competitions. The winning entry of the contest is also explained in detail. This controller is based on the Monte Carlo Tree Search algorithm, and employed Covariance Matrix Adaptation Evolution Strategy (CMA-ES) for parameter tuning.
Keywords :
Monte Carlo methods; artificial intelligence; covariance matrices; game theory; search problems; travelling salesman problems; 2013 IEEE Conference on Computational Intelligence in Games; CMA-ES; MO-PTSP competition; Monte Carlo tree search algorithm; artificial intelligence competitions; covariance matrix adaptation evolution strategy; multiobjective physical travelling salesman problem competition; parameter tuning; Artificial intelligence; Educational institutions; Fuels; Games; Marine vehicles; Real-time systems; Vectors;
Conference_Titel :
Evolutionary Computation (CEC), 2014 IEEE Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6626-4
DOI :
10.1109/CEC.2014.6900243