Suggested Reading for Chapter Six: Popular Evolutionary Algorithm Variants

Genetic Algorithms

  • Kenneth De Jong Genetic algorithms are NOT function optimizers.
    Ppages 5–18 in L.D. Whitley, editor. Foundations of Genetic Algorithms – 2. Morgan Kauf-
    mann, San Francisco, 1993.
  • D.E. Goldberg. Genetic Algorithms in Search, Optimization and Machine
    Addison-Wesley, 1989.Hugely influential book in the field of AI, that first brought EAs to many people;s attention
  • J.H. Holland. Adaption in Natural and Artificial Systems. MIT Press, 1992, First edition: 1975, University of Michigan Press.
  • M.~Mitchell. An Introduction to Genetic Algorithms.
    MIT Press, 1996.

Evolution Strategies

  • T. Bäck. Evolutionary Algorithms in Theory and Practice. Oxford University Press, New York, 1996.
  • T. Bäck, D.B. Fogel, and Z.~Michalewicz, editors. Evolutionary Computation 1: Basic Algorithms and Operators.
    Institute of Physics Publishing, 2000.
  • T. Bäck, D.B. Fogel, and Z.~Michalewicz, editors. Evolutionary Computation 2: Advanced Algorithms and Operators. Institute of Physics Publishing, 2000.
  • Hans-Georg Beyer. The Theory of Evolution Strategies. Springer, Berlin, 2001.
  • H.-G. Beyer and H.-P. Schwefel. Evolution strategies: A comprehensive introduction. Natural Computing, 1(1):3–52, 2002.
  • H.-P. Schwefel. Evolution and Optimum Seeking. Wiley, New York, 1995.

Evolutionary Programming

  • L.J. Fogel, A.J. Owens, M.J. Walsh. Artificial Intelligence Through Simulated Evolution. John Wiley, 1966
  • D.B. Fogel.  Evolutionary Computation.  IEEE Press, Piscataway, NJ, 1995
  • T. Bäck, G.~Rudolph, H.-P.~Schwefel. Evolutionary programming and evolution strategies: Similarities and differences.In Fogel, Atmar Eds. Proceedings of EP-93, pp. 11–22
  • D.B.~Fogel. Blondie24: Playing at the Edge of AI. Morgan Kaufmann, San Francisco, 2002

Genetic Programming

  • J.R. Koza. Genetic Programming.  MIT Press, 1992.
  • J.R. Koza.  Genetic Programming II. MIT Press, 1994.
  • W. Banzhaf, P. Nordin, R.E. Keller, and F.D. Francone.  Genetic Programming: An Introduction. Morgan Kaufmann, 1998.
  • W.B. Langdon.  Genetic Programming + Data Structures = Automatic Programming!  Kluwer, 1998.
  • W.B. Langdon and R. Poli.  Foundations of Genetic Programming.  Springer-Verlag, 2001.

Learning Classifier Systems

  • P.L. Lanzi, W. Stolzmann, and S.W. Wilson, editors:  Learning Classifier Systems: From Foundations to Applications, volume 1813 of  LNAI. Springer-Verlag, Berlin, 2000.
  • J.H. Holland, L.B. Booker, M. Colombetti, M. Dorigo, D.E. Goldberg, S. Forrest, R.L. Riolo, R.E. Smith, P.L. Lanzi, W.~Stolzmann, and S.W. Wilson.  What is a learning classifier system?
    In Lanzi et al. above, pages 3–32.
  • J.H. Holmes, P.L. Lanzi, W. Stolzmann, and S.W. Wilson. Learning classifier systems: new models, successful applications. Information Processing Letters, 82(1):23–30, 2002.
  • P.L. Lanzi. Learning classifier systems: then and now. Evolutionary Intelligence}, 1(1):63-82 2008.

Differential Evolution

  • R. Storn and K.Price. Differential evolution – a simple and efficient adaptive scheme for global optimization over continuous spaces. Technical Report TR-95-012, ICSI, Berkeley, March 1995.
  • K.V. Price, R.N. Storn, and J.A. Lampinen. Differential Evolution: A Practical Approach to Global Optimization. Natural Computing Series. Springer, 2005.

Particle Swarm Optimization

  • J. Kennedy and R.C. Eberhart. Swarm Intelligence. Morgan Kaufmann, 2001.
  • R. Poli, J. Kennedy, and T. Blackwell. Particle swarm optimization — an overview. Swarm Intelligence, 1(1):33–57, 2007.

Estimation of Distribution Algorithms

  • M. Pelikan, D.E. Goldberg, F.Lobo. A survey of optimization by building and using probabilistic models. Tech. rep., Illinois Genetic Algorithms Laboratory, University of Illinois at Urbana-Champaign, 1999
  • P.Larranaga, J.A. Lozano, Eds.Estimation of Distribution Algorithms: a New tool for Evolutionary Computation Kluwer Academic Publishers, Boston, 2002
  • J.A. Lozano, P. Larranaga, Eds. Towards a New Evolutionary Computation : Advances in Estimation of
    Distribution Algorithms
    Springer, Berlin, Heidelberg, New York, 2006
  • M.Pelikan. Hierarchical Bayesian Optimization Algorithm: Toward a New
    Generation of Evolutionary Algorithms
    Springer, Berlin, Heidelberg, New York, 2006
  • M. Pelikan, K. Sastry, E. Cantu-Paz, Eds. Scalable Optimization via Probabilistic Modeling: From
    Algorithms to Applications
    . Springer, Berlin, Heidelberg, New York, 2006

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