Abstract
Elastic nets (EN) have been effectively used in the traveling salesman problem (TSP), the prediction problem of protein structure, and so on. Nevertheless the limitations of the EN theory and its architecture seriously prevent the EN approach from the application for problem-solving of multi-agent systems (MAS) and computer networks (CN). This paper presents a crossbar composite spring-nets (CCSN) approach to MAS and CN, which transforms the optimization problem of MAS and CN into the evolutionary dynamics of crossbar composite spring nets. The CCSN approach is essentially different from EN and has many advantages over EN in terms of the problem-solving performance and the suitability for complex environment in MAS and CN.
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Shuai, D. (2008). Crossbar Composite Spring-Nets to Optimize Multi-Agent Systems and Computer Networks. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2008. Lecture Notes in Computer Science(), vol 5227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85984-0_66
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DOI: https://doi.org/10.1007/978-3-540-85984-0_66
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