Skip to main content

Part of the book series: Natural Computing Series ((NCS))

Abstract

In most of this book we have been concerned with problems where the quality of a proposed solution can be relatively easily measured in isolation by some externally provided fitness function. Evaluating a solution may involve an element of random noise, but does not particularly depend on the context in which it is done. However, there are two obvious scenarios in which this set-up does not really hold. The first occurs when a solution represents some strategy or design that works in opposition to some competitor that is itself adapting. The most obvious example here would be adversarial game-playing such as chess. The second comes about when a solution being evolved does not represent a complete solution to a problem, but instead can only be evaluated as part of a greater whole, that together accomplishes some task. An example might be the evolution of a set of traffic-light controllers, each to be sited on a different junction, with fitness reflecting their joint performance in reducing congestion over a day’s simulated traffic. Both of these are examples of coevolution. This chapter gives an overview of the types of scenarios where coevolution might be usefully applied, and of some of the issues involved in designing a successful application.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 49.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 49.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Eiben, A.E., Smith, J.E. (2015). Coevolutionary Systems. In: Introduction to Evolutionary Computing. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44874-8_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-44874-8_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-44873-1

  • Online ISBN: 978-3-662-44874-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics