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The Emergence of Social Learning in Artificial Societies

Part of the Lecture Notes in Computer Science book series (LNCS,volume 2611)

Abstract

The most recent advances of artificial life research are opening up a new frontier: the creation of simulated life environments populated by autonomous agents. In several cases a new paradigm for learning is emerging: social learning as a form of self-organization of many individual learning. In this paper two different approaches are presented and discussed: genetic competition and partial emulation. Finally an example of application of these concepts.

Keywords

  • Social Learning
  • Autonomous Agent
  • Artificial Life
  • Direct Competition
  • Artificial World

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Annunziato, M., Pierucci, P. (2003). The Emergence of Social Learning in Artificial Societies. In: , et al. Applications of Evolutionary Computing. EvoWorkshops 2003. Lecture Notes in Computer Science, vol 2611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36605-9_43

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  • DOI: https://doi.org/10.1007/3-540-36605-9_43

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00976-4

  • Online ISBN: 978-3-540-36605-8

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