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Article type: Research Article
Authors: Dehimi, Nour El Houda* | Guerram, Tahar | Tolba, Zakaria
Affiliations: Department of Mathematics and Computer Science, University of Oum El Bouaghi, Algeria
Correspondence: [*] Corresponding author: Nour El Houda Dehimi, Department of Mathematics and Computer Science, University of Oum El Bouaghi, Algeria. E-mail: [email protected].
Abstract: In this work, we propose a new approach for coordinating generated agents’ plans dynamically. The purpose is to take into consideration new conflicts introduced in new versions of agents’ plans. The approach consists in finding the best combination which contains one plan for each agent among its set of possible plans whose execution does not entail any conflict. This combination of plans is reconstructed dynamically, each time agents decide to change their plans to take into account unpredictable changes in the environment. This not only ensures that new conflicts are likely to be introduced in the new plans that are taken into account but also it allows agents to deal, solely, with the execution of their actions and not with the resolution of conflicts. For this, we use genetic algorithms where the proposed fitness function is defined based on the number of conflicts that agents can experience in each combination of plans. As part of our work, we used a concrete case to illustrate and show the usefulness of our approach.
Keywords: Multi-agent systems, distributed dynamic planning, coordination, genetic algorithms
DOI: 10.3233/MGS-220304
Journal: Multiagent and Grid Systems, vol. 18, no. 3-4, pp. 219-239, 2022
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