Abstract
Robots play an important role in space exploration whereby the presence of human is almost impossible in some environments. Instead of using a robot, we incorporate a group of robots working together to achieve the definitive goal. Evolutionary algorithm, namely Genetic Algorithm is applied in the multi-agent robotics for space exploration. Hereby, the core focus of this paper is to study the effect of crossover rate upon the convergence of the exploration. As from our results, choosing the right parameter value is crucial for optimal coverage of the potential area. © IFIP International Federation for Information Processing 2012.
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Ting, T. O., Wan, K., Man, K. L., & Lee, S. (2012). Space exploration of multi-agent robotics via genetic algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7513 LNCS, pp. 500–507). https://doi.org/10.1007/978-3-642-35606-3_59
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