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Exploring Component-based Representations - The Secret of Creativity by Evolution?

  • Peter J. Bentley

Abstract

This paper investigates one of the newest and most exciting methods in computer science to date: employing computers as creative problem solvers by using evolution to explore for new solutions. The paper introduces and discusses the new understanding that explorative evolution relies upon a representation based on components rather than a parameterisation of a known solution. Evolution explores how the components can be arranged, how many are needed, and the type or function of each. The extra freedom provided by this simple idea is remarkable. By using evolutionary computation for exploration instead of optimisation, this technique enables us to expand the capabilities of computers. The paper describes how the approach has already shown impressive results in the creation of novel designs and architecture, fraud detection, composition of music, and creation of art. A framework for explorative evolution is provided, with discussion of the significance and difficulties posed by each element. The paper ends with an example of creative problem solving for a simple application - showing how evolution can shape pieces of paper to make them fall slowly through the air, by spiraling down like sycamore seeds.

Keywords

Genetic Algorithm Evolutionary Algorithm Fitness Function Genetic Programming Genetic Representation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London 2000

Authors and Affiliations

  • Peter J. Bentley
    • 1
  1. 1.Department of Computer ScienceUniversity College LondonUK

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