Adaptive Computation Paradigm in Knowledge Representation: Traditional and Emerging Applications

Marina L. Gavrilova

doi:10.4018/jssci.2009010106

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Adaptive Computation Paradigm in Knowledge Representation: Traditional and Emerging Applications

Marina L. Gavrilova (University of Calgary, Canada)

Source Title: International Journal of Software Science and Computational Intelligence (IJSSCI) 1(1)

DOI: 10.4018/jssci.2009010106

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Abstract

The constant demand for complex applications, the ever increasing complexity and size of software systems, and the inherently complicated nature of the information drive the needs for developing radically new approaches for information representation. This drive is leading to creation of new and exciting interdisciplinary fields that investigate convergence of software science and intelligence science, as well as computational sciences and their applications. This survey article discusses the new paradigm of the algorithmic models of intelligence, based on the adaptive hierarchical model of computation, and presents the algorithms and applications utilizing this paradigm in data-intensive, collaborative environment. Examples from the various areas include references to adaptive paradigm in biometric technologies, evolutionary computing, swarm intelligence, robotics, networks, e-learning, knowledge representation and information system design. Special topics related to adaptive models design and geometric computing are also included in the survey.

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Adaptive Computation Paradigm in Knowledge Representation: Traditional and Emerging Applications

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