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Evaluating the evolvability of emergent agents with different numbers of states

Published: 08 July 2009 Publication History

Abstract

Emergence is an important and promising scientific topic today because it offers benefits that can not be achieved by classic means. But it is often challenging to control emergence and to find correct local rules that create desired global behavior. It especially becomes difficult if the search space representing the problem that has to be optimized is not continuous/linear. One solution to that problem is evolution. This paper shows that the use of Genetic Algorithms is feasible for such problems by the example of the Creatures' Exploration Problem in which agents shall visit all non-blocked cells in a grid. Different amounts of agents and states per agent are evolved and statistically compared. It shows that neither a single extension of agent capabilities nor sole increase of agent numbers provides the best performance. The results hint that a mixture of both should be used instead.

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Cited By

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  • (2010)Revising the trade-off between the number of agents and agent intelligenceProceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I10.1007/978-3-642-12239-2_4(31-40)Online publication date: 7-Apr-2010

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  1. Evaluating the evolvability of emergent agents with different numbers of states

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      cover image ACM Conferences
      GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation
      July 2009
      2036 pages
      ISBN:9781605583259
      DOI:10.1145/1569901

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 08 July 2009

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      Author Tags

      1. cellular automata
      2. fitness landscape
      3. genetic algorithms
      4. multi-agent systems
      5. optimization

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      GECCO09
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      GECCO09: Genetic and Evolutionary Computation Conference
      July 8 - 12, 2009
      Québec, Montreal, Canada

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      Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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      • (2010)Revising the trade-off between the number of agents and agent intelligenceProceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I10.1007/978-3-642-12239-2_4(31-40)Online publication date: 7-Apr-2010

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