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Modeling Higher-Order Adaptive Evolutionary Processes by Multilevel Adaptive Agent Models

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PRIMA 2019: Principles and Practice of Multi-Agent Systems (PRIMA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11873))

Abstract

In this paper a fourth-order adaptive agent model based on a multilevel reified network model is introduced to describe different orders of adaptivity of the agent?s biological embodiment, as found in a case study on evolutionary processes. The adaptive agent model describes how the causal pathways for newly developed features affect the causal pathways of already existing features. This makes these new features one order of adaptivity higher than the existing ones. A network reification approach is shown to be an adequate means to model this.

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Author information

Authors and Affiliations

  1. Social AI Group, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Jan Treur

Authors
  1. Jan Treur
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Correspondence to Jan Treur .

Editor information

Editors and Affiliations

  1. Università degli Studi di Torino, Turin, Italy

    Matteo Baldoni

  2. Utrecht University, Utrecht, The Netherlands

    Mehdi Dastani

  3. Zhejiang University, Hangzhou, China

    Beishui Liao

  4. National Institute of Advanced Industrial Science and Technology, Tokyo, Japan

    Yuko Sakurai

  5. University of Texas at Dallas, Richardson, TX, USA

    Rym Zalila Wenkstern

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Treur, J. (2019). Modeling Higher-Order Adaptive Evolutionary Processes by Multilevel Adaptive Agent Models. In: Baldoni, M., Dastani, M., Liao, B., Sakurai, Y., Zalila Wenkstern, R. (eds) PRIMA 2019: Principles and Practice of Multi-Agent Systems. PRIMA 2019. Lecture Notes in Computer Science(), vol 11873. Springer, Cham. https://doi.org/10.1007/978-3-030-33792-6_35

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  • DOI: https://doi.org/10.1007/978-3-030-33792-6_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33791-9

  • Online ISBN: 978-3-030-33792-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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