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Evolvable Agents: A Framework for Peer-to-Peer Evolutionary Algorithms

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Parallel and Distributed Computational Intelligence

Part of the book series: Studies in Computational Intelligence ((SCI,volume 269))

Abstract

Distributed evolutionary computation programs often needs increasingly big amounts of computational power when tackling large instances of hard optimization problems, and Peer-to-Peer (P2P) systems could be an option for building the large virtual supercomputer in which they could be run. Even as distributed Evolutionary Algorithms (EA) do take advantage of parallel execution by simultaneously promoting diversity and reducing runtime, there are still many challenges on the parallelization of EAs in P2P systems. In this chapter we present a survey of the state of the art in P2P EAs and our solutions to the main P2P issues such as decentralization, massive scalability and fault tolerance.

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Authors and Affiliations

  1. Department of Architecture and Computer Technology, University of Granada, Spain

    Juan Luis Jimenez Laredo, Juan Julian Merelo Guervos & Pedro Angel Castillo Valdivieso

Authors
  1. Juan Luis Jimenez Laredo
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  2. Juan Julian Merelo Guervos
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  3. Pedro Angel Castillo Valdivieso
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Editor information

Editors and Affiliations

  1. University of Extremadura, C/ Sta Teresa de Jornet, 38, Merida, Spain

    Francisco Fernández de Vega

  2. Yahoo! Inc., 701 First Avenue, 94087, Sunnyvale, CA, USA

    Erick Cantú-Paz

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Jimenez Laredo, J.L., Merelo Guervos, J.J., Castillo Valdivieso, P.A. (2010). Evolvable Agents: A Framework for Peer-to-Peer Evolutionary Algorithms. In: de Vega, F.F., Cantú-Paz, E. (eds) Parallel and Distributed Computational Intelligence. Studies in Computational Intelligence, vol 269. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10675-0_3

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  • DOI: https://doi.org/10.1007/978-3-642-10675-0_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10674-3

  • Online ISBN: 978-3-642-10675-0

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