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Adapting Populations of Agents

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Book cover Adaptive Agents and Multi-Agent Systems (AAMAS 2002, AAMAS 2001)

Abstract

We control a population of interacting software agents. The agents have a strategy, and receive a payoff for executing that strategy. Unsuccessful agents become extinct. We investigate the repercussions of maintaining a diversity of agents. There is often no economic rationale for this. If maintaining diversity is to be successful, i.e. without lowering too much the payoff for the non-endangered strategies, it has to go on forever, because the non-endangered strategies still get a good payoff, so that they continue to thrive, and continue to endanger the endangered strategies. This is not sustainable if the number of endangered ones is of the same order as the number of non-endangered ones. We also discuss niches, islands. Finally, we combine learning as adaptation of individual agents with learning via selection in a population.

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References

  1. Gary S. Becker. Altruism, egoism, and genetic fitness: Economics and sociobiology. In The Economic Approach to Human Behavior, pages 282–294. University of Chicago Press, Chicago, 1976.

    Google Scholar 

  2. T. Borgers and R. Sarin. Learning through reinforcement and replicator dynamics. Journal of Economic Theory, 77:1–14, 1997.

    Article  MathSciNet  Google Scholar 

  3. Andrea Cavagna, Juan P. Garrahan, Irene Giardina, and David Sherrington. Thermal model for adaptive competition in a market. Physical Review Letters, 83:4429–4432, 1999.

    Article  Google Scholar 

  4. Philippe De Wilde. Neural Network Models, second expanded edition. Springer Verlag, London, 1997.

    Google Scholar 

  5. Philippe De Wilde. How soft games can be played. In H.-J. Zimmermann, editor, EUFIT’ 99, 7th European Congress on Intelligent Techniques & Soft Computing, pages FSD-6-12698, Aachen, September 1999. Verlag Mainz.

    Google Scholar 

  6. Philippe De Wilde, Hyacinth S. Nwana, and Lyndon C. Lee. Stability, fairness and scalability of multi-agent systems. International Journal of Knowledge-Based Intelligent Engineering Systems, 3(2):84–91, 1999.

    Google Scholar 

  7. Drew Fudenberg and David K. Levine. The Theory of Learning in Games. MIT Press, Cambridge, Massachusetts, 1998.

    MATH  Google Scholar 

  8. B. A. Huberman, editor. The Ecology of Computation. North-Holland, Amsterdam, 1988.

    MATH  Google Scholar 

  9. Nicholas J. Jennings. On agent-based software engineering. Artificial Intelligence, 117:277–296, 2000.

    Article  MATH  Google Scholar 

  10. John Pezzey. Economic analysis of sustainable growth and sustainable development. World Bank, Washington DC, 1989.

    Google Scholar 

  11. Andy Purvis and Andy Hector. Getting the measure of biodiversity. Nature, 405:212–219, 20.

    Google Scholar 

  12. John Maynard Smith. Evolutionary Genetics. Oxford University Press, Oxford, 1998.

    Google Scholar 

  13. S. M. Stanley. Macroevolution. W. H. Freeman, San Fransisco, 1979.

    Google Scholar 

  14. Jörgen W. Weibull. Evolutionary Game Theory. MIT Press, Cambridge, Massachusetts, 1995.

    MATH  Google Scholar 

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© 2003 Springer-Verlag Berlin Heidelberg

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De Wilde, P. et al. (2003). Adapting Populations of Agents. In: Alonso, E., Kudenko, D., Kazakov, D. (eds) Adaptive Agents and Multi-Agent Systems. AAMAS AAMAS 2002 2001. Lecture Notes in Computer Science(), vol 2636. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44826-8_7

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  • DOI: https://doi.org/10.1007/3-540-44826-8_7

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40068-4

  • Online ISBN: 978-3-540-44826-6

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