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Moshe Sipper

    Moshe Sipper is een auteur die zijn expertise op het gebied van kunstmatige intelligentie combineert met artistiek talent. Zijn werken duiken vaak in complexe concepten en bieden een uniek perspectief op de kruising van technologie en menselijke ervaring. Als zowel een ervaren academicus als een maker, onderscheidt Sipper zich door zijn vermogen om ingewikkelde ideeën te vertalen naar toegankelijke en tot nadenken stemmende verhalen.

    Evolvable systems
    Evolution of parallel cellular machines
    • Evolution of parallel cellular machines

      The Cellular Programming Approach

      4,7(3)Tarief

      Collective systems, abounding in nature, have evolved by natural selection to exhibit striking problem-solving capacities. Employing simple yet versatile parallel cellular models, coupled with evolutionary computation techniques, this volume explores the issue of constructing man-made systems that exhibit characteristics like those occuring in nature. Parallel cellular machines hold potential both scientifically, as vehicles for studying phenomena of interest in areas such as complex adaptive systems and artificial life, and practically, enabling the construction of novel systems, endowed with evolutionary, reproductive, regenerative, and learning capabilities. This volume examines the behavior of such machines, the complex computation they exhibit, and the application of artificial evolution to attain such systems.

      Evolution of parallel cellular machines
    • Evolvable systems

      • 382bladzijden
      • 14 uur lezen

      This book constitutes the refereed proceedings of the Second International Conference on Evolvable Systems: From Biology to Hardware, ICES '98, held in Lausanne, Switzerland in September 1998. The 38 revised papers presented were carefully selected for inclusion in the book from numerous submissions. The papers are organized in topical sections on evaluation of digital systems, evolution of analog systems, embryonic electronics, bio-inspired systems, artifical neural networks, adaptive robotics, adaptive hardware platforms, and molecular computing.

      Evolvable systems