Solving strategy board games using a CSP-based ACO approach
by Antonio Gonzalez-Pardo; Javier Del Ser; David Camacho
International Journal of Bio-Inspired Computation (IJBIC), Vol. 10, No. 2, 2017

Abstract: In the last years, there have been a huge increase in the number of research contributions that use games and video-games as an application domain for testing different artificial intelligence algorithms. Some of these problems can be represented as a constraint satisfaction problem (CSP), and heuristics algorithms (such as ant colony optimisation) can be used due to the complexity of the modelled problems. This paper presents a comparative study of the performance of a novel ACO model for CSP-based board games. In this work, two different oblivion rate meta-heuristics for controlling the number of pheromones created in the model have been created. Experimental results reveal that both meta-heuristics reduce considerably the number of pheromones produced in the system without affecting the quality of the solutions in terms of average optimality.

Online publication date: Fri, 18-Aug-2017

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