Abstract
Soft computing (SC) techniques such as fuzzy logic (FL), neural networks (NN), and genetic algorithms (GA) are complementary. Each SC technique has particular computational properties that make them suited for particular problems and not for others. Thus, in solving complex, real-world problems, we need to incorporate some SC techniques into the application systems to increase the systems’ “intelligence”. In this paper, we first propose an agent-based framework for integrating SC techniques into practical application systems. We then discuss the design and implementation of a platform independent soft computing support environment based on the framework. We call such an environment agent-based softcomputing society. Such a society can facilitate the design of truly robust, flexible and adaptive hybrid intelligent systems.
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Zhang, C., Zhang, Z., San, O.S. (2001). An Agent-Based Soft Computing Society. In: Ziarko, W., Yao, Y. (eds) Rough Sets and Current Trends in Computing. RSCTC 2000. Lecture Notes in Computer Science(), vol 2005. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45554-X_84
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DOI: https://doi.org/10.1007/3-540-45554-X_84
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