Abstract
With the properties of T-coloring problems in mind, multiagent systems and evolutionary algorithms are integrated to form a new algorithm, Multiagent Evolutionary Algorithm for T-coloring (MAEA-T-coloring). We studied the generalization of classical graph coloring model, and focused our interest in the restricted T-coloring. An agent in MAEA-T-coloring represents a candidate solution to T-colorings. All agents live in a latticelike environment, with each agent fixed on a lattice-point. In order to increase energies, they compete or cooperate with their neighbors using their knowledge. Experiments on large random instances of T-colorings show encouraging results about MAEA- T-coloring.
This work was supported by the National Natural Science Foundations of China under Grant 60502043, 60872135, and 60602064, the Program for New Century Excellent Talents in University of China under Grant NCET-06-0857, the National High Technology Research and Development Program (“863” program) of China under Grant 2006AA01Z107, and the Natural Science Research Project of Shaanxi, China.
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Liu, J., Zhong, W., Li, J. (2008). Multiagent Evolutionary Algorithm for T-coloring Problem. In: Li, X., et al. Simulated Evolution and Learning. SEAL 2008. Lecture Notes in Computer Science, vol 5361. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89694-4_30
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DOI: https://doi.org/10.1007/978-3-540-89694-4_30
Publisher Name: Springer, Berlin, Heidelberg
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