David B. Fogel

  • Genetic Programming 1996

    Genetic Programming 1996

    Proceedings of the First Annual Conference, July 28-31, 1996, Stanford University

    John R. Koza, David E. Goldberg, David B. Fogel, and Rick L. Riolo

    Genetic programming is a domain-independent method for automatic programming that evolves computer programs that solve, or approximately solve, problems. Starting with a primordial ooze of thousands of randomly created computer programs composed of functions and terminals appropriate to a problem, a population of programs is progressively evolved over many generations using the Darwinian principle of survival of the fittest, a sexual recombination operation, and occasional mutation.

    These proceedings of the first Genetic Programming Conference present the most recent research in the field of genetic programming as well as recent research results in the fields of genetic algorithms, evolutionary programming, and learning classifier systems.

    Topics include: Applications of genetic programming. Theoretical foundations of genetic programming. Implementation issues. Technique extensions. Automated synthesis of analog electrical circuits. Automatic programming of cellular automata. Induction. System identification. Control. Evolution of machine language programs. Automatic programming of multi-agent strategies. Automated evolution of program architecture. Evolution of mental models. Implementations of memory and state. Cellular encoding. Evolvable hardware. Parallelization techniques. Relations to biology and cognitive systems. Genetic algorithms. Evolutionary programming. Evolution strategies. Learning classifier systems.

    Complex Adaptive Systems series.

    A Bradford Book

    • Paperback $85.00
  • Evolutionary Programming IV

    Evolutionary Programming IV

    Proceedings of the Fourth Annual Conference on Evolutionary Programming

    John R. McDonnell, Robert G. Reynolds, and David B. Fogel

    March 1-3, 1995, San Diego, California Evolutionary programming is one of the predominate algorithms withing the rapidly expanding field of evolutionary computation. These edited contributions to the Fourth Annual Conference on Evolutionary Programming are by leading scientists from academia, industry, and defense. The papers describe both the theory and practical application of evolutionary programming, as well as other methods of evolutionary computation including evolution strategies, genetic algorithms, genetic programming, and cultural algorithms.

    Topics include :- Novel Areas of Evolutionary Programming and Evolution Strategies.- Evolutionary Computation with Medical Applications.- Issues in Evolutionary Optimization Pattern Discovery, Pattern Recognition, and System Identification.- Hierarchical Levels of Learning.- Self-Adaptation in Evolutionary Computation.- Morphogenic Evolutionary Computation.- Issues in Evolutionary Optimization.- Evolutionary Applications to VLSI and Part Placement.- Applications of Evolutionary Computation to Biology and Biochemistry Control.- Applications of Evolutionary Computation.- Genetic and Inductive Logic Programming.- Genetic Neural Networks.- The Future of Evolutionary Computation. A Bradford Book. Complex Adaptive Systems series

    • Hardcover $20.75