RT Journal Article
T1 Solving strategy board games using a CSP-based ACO approach
A1 Gonzalez-Pardo, Antonio
A1 Ser, Javier Del
A1 Camacho, David
AB 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.
SN 1758-0366
YR 2017
FD 2017
LK https://hdl.handle.net/11556/4081
UL https://hdl.handle.net/11556/4081
LA eng
NO Gonzalez-Pardo , A , Ser , J D & Camacho , D 2017 , ' Solving strategy board games using a CSP-based ACO approach ' , International Journal of Bio-Inspired Computation , vol. 10 , no. 2 , pp. 136-144 . https://doi.org/10.1504/IJBIC.2017.085892
NO Publisher Copyright: Copyright © 2017 Inderscience Enterprises Ltd.
NO This work is supported by the Spanish Ministry of Science and Education under Project Code TIN2014-56494-C4-4-P, Comunidad Autonoma de Madrid under project CIBERDINE S2013/ICE-3095, and Savier an Airbus Defense and Space project (FUAM-076914 and FUAM-076915).
DS TECNALIA Publications
RD 28 jul 2024