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IEEE Computational Intelligence Magazine

Issue 4 • Date Nov. 2006

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Displaying Results 1 - 25 of 25
  • IEEE Computational Intelligence Magazine - Nov. 2006

    Publication Year: 2006, Page(s): c1
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  • IEEE Member Digital Library [advertisement]

    Publication Year: 2006, Page(s): c2
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  • Table of contents - Vol 1 No 4

    Publication Year: 2006, Page(s): 1
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  • Year-end review [Editor's Remarks]

    Publication Year: 2006, Page(s): 2
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  • IEEE/CIS Publications Activities [President's Message]

    Publication Year: 2006, Page(s):3 - 4
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  • Call for Papers - 2007 International Joint Conference on Neural Neworks

    Publication Year: 2006, Page(s): 5
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  • Visualizing the computational intelligence field [Application Notes]

    Publication Year: 2006, Page(s):6 - 10
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1719 KB) | HTML iconHTML

    In this paper, we visualize the structure and the evolution of the computational intelligence (CI) field. Based on our visualizations, we analyze the way in which the CI field is divided into several subfields. The visualizations provide insight into the characteristics of each subfield and into the relations between the subfields. By comparing two visualizations, one based on data from 2002 and o... View full abstract»

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  • Call for Papers - IEEE Congress on Evolutionary Computation 2007

    Publication Year: 2006, Page(s): 11
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  • Introducing the CIS Technical Activities [Society Briefs]

    Publication Year: 2006, Page(s):12 - 17
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  • IEEE/CIS Tour de China [Family Corner]

    Publication Year: 2006, Page(s):15 - 17
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  • Foraging theory for multizone temperature control

    Publication Year: 2006, Page(s):18 - 27
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (4037 KB) | HTML iconHTML

    Models from behavioral ecology, specifically foraging theory, are used to describe the decisions an animal forager must make in order to maximize its rate of energy gain and thereby improve its survival probability. Using a bioinspired methodology, we view an animal as a software agent, the foraging landscape as a spatial layout of temperature zones, and nutrients as errors between the desired and... View full abstract»

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  • Ant colony optimization

    Publication Year: 2006, Page(s):28 - 39
    Cited by:  Papers (453)  |  Patents (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1238 KB) | HTML iconHTML

    Swarm intelligence is a relatively new approach to problem solving that takes inspiration from the social behaviors of insects and of other animals. In particular, ants have inspired a number of methods and techniques among which the most studied and the most successful is the general purpose optimization technique known as ant colony optimization. Ant colony optimization (ACO) takes inspiration f... View full abstract»

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  • Advances in artificial immune systems

    Publication Year: 2006, Page(s):40 - 49
    Cited by:  Papers (194)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1363 KB) | HTML iconHTML

    During the last decade, the field of artificial immune system (A1S) is progressing slowly and steadily as a branch of computational intelligence (CI). There has been increasing interest in the development of computational models inspired by several immunological principles. In particular, some are building models mimicking the mechanisms in the biological immune system (BIS) to better understand i... View full abstract»

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  • Evolutionary computation benchmarking repository [Developmental Tools]

    Publication Year: 2006, Page(s):50 - 60
    Cited by:  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (604 KB) | HTML iconHTML

    Evolutionary computation has been used with great success for the solution of hard optimization problems. Theoretical analysis, although important in its own right, e.g. for understanding underlying phenomena and characteristics of evolutionary search, can only provide upper and/or lower bounds of performance estimation of evolutionary algorithms for hard optimization problems. In practice, empiri... View full abstract»

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  • George Friedman-evolving circuits for robots [Historic Perspective]

    Publication Year: 2006, Page(s):52 - 54
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (253 KB) | HTML iconHTML

    Many years ago, George Friedman analyzed this problem and developed what was, in essence, a blueprint for designing an adaptive neural control circuit for mobile robots based on natural selection. Friedman's objective was to investigate the possibility of borrowing from nature to develop goal-seeking machines. He noted that in a constant environment, natural evolutionary processes lead to a series... View full abstract»

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  • 2007 CIS Neural Networks Pioneer Award - Michael Jordan

    Publication Year: 2006, Page(s): 55
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  • 2007 CIS Fuzzy Systems Pioneer Award - James Keller

    Publication Year: 2006, Page(s): 55
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  • 2007 CIS Fuzzy Systems Pioneer Award - George Klir

    Publication Year: 2006, Page(s): 56
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  • 2007 CIS Meritorious Service Award - David B. Fogel

    Publication Year: 2006, Page(s): 56
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  • 2007 CIS Outstanding Chapter Award

    Publication Year: 2006, Page(s): 57
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  • Knowledge Incorporation in Evolutionary Computation [Book Review]

    Publication Year: 2006, Page(s):58 - 59
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  • Conference Calendar

    Publication Year: 2006, Page(s): 60
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  • 2006 Index IEEE Computational Intelligence Magazine - Vol. 1

    Publication Year: 2006, Page(s):62 - 64
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  • FUZZ-IEEE 2007 - Call for Papers

    Publication Year: 2006, Page(s): c3
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  • Introducing the IEEE Power & Energy Library

    Publication Year: 2006, Page(s): c4
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Aims & Scope

The IEEE Computational Intelligence Magazine (CIM) publishes peer-reviewed articles that present emerging novel discoveries, important insights, or tutorial surveys in all areas of computational intelligence design and applications, in keeping with the Field of Interest of the IEEE Computational Intelligence Society (IEEE/CIS). 

Full Aims & Scope