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Divide to Coordinate: Coevolutionary Problem Solving

Author

Listed:
  • Stuart Kauffman
  • William G. Macready
  • Emily Dickinson

Abstract

Optimization of systems with many conflicting constraints arises in numerous settings. Common optimization procedures seek to improve performance of the system as a whole. We show that coevolutionary problem solving, in which a system is partitioned into subsystems each of which selfishly optimizes, can lead to enhanced performance as a collective emergent property. Optimally partitioned systems often lie near a transistion from order to chaos.

Suggested Citation

  • Stuart Kauffman & William G. Macready & Emily Dickinson, 1994. "Divide to Coordinate: Coevolutionary Problem Solving," Working Papers 94-06-031, Santa Fe Institute.
  • Handle: RePEc:wop:safiwp:94-06-031
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    Cited by:

    1. Karén Hovhannisian & Marco Valente, 2005. "Modeling Directed Local Search Strategies on Technology," Computational Economics 0507001, University Library of Munich, Germany.
    2. Bennett Levitan & Jose Lobo & Stuart Kauffman & Richard Schuler, 1999. "Optimal Organization Size in a Stochastic Environment with Externalities," Working Papers 99-04-024, Santa Fe Institute.
    3. Karén Hovhannissian & Marco Valente, 2004. "Modeling Directed Local Search Strategies on Technology Landscapes: Depth and Breadth," ROCK Working Papers 028, Department of Computer and Management Sciences, University of Trento, Italy, revised 17 Jun 2008.
    4. Bill McKelvey, 1999. "Avoiding Complexity Catastrophe in Coevolutionary Pockets: Strategies for Rugged Landscapes," Organization Science, INFORMS, vol. 10(3), pages 294-321, June.
    5. Jürgen Mihm & Christoph Loch & Arnd Huchzermeier, 2003. "Problem--Solving Oscillations in Complex Engineering Projects," Management Science, INFORMS, vol. 49(6), pages 733-750, June.
    6. Karén Hovhannisian, 2004. "Imperfect Local Search Strategies on Technology Landscapes: Satisficing, Deliberate Experimentation and Memory Dependence," Computational Economics 0405009, University Library of Munich, Germany.
    7. Svenja C. Sommer & Christoph H. Loch, 2004. "Selectionism and Learning in Projects with Complexity and Unforeseeable Uncertainty," Management Science, INFORMS, vol. 50(10), pages 1334-1347, October.

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