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Robust Collaboration: Enriching Decisions with Abstract Preferences

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Engineering Multi-Agent Systems (EMAS 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8758))

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Abstract

Aspects of human societies provide a rich source of inspiration for influencing individual and social behaviors in order to achieve collaboration in a MAS. This article particularly investigates how human cultures and particularly human values can be used as an inspiration for achieving collaboration. Indeed, human values abstractly set what individuals consider as important, driving them towards similar individual and social outcomes, helping them to work together. We want to reproduce the same type of behaviors in MASs, even if we do not aim at faithfully reproducing human behavior.

Preferences are used for modeling values. But, specifically for values, preference functions order abstract yet driving criteria (e.g. “security vs. freedom” instead of “blue vs. red”). Values support abstract decisions, which drive agents to make local decisions that support some coherence at the collective level.

We show that integrating values as a design constraint have many benefits for designing collaborative MAS. In particular, they offer greater flexibility and robustness to the system. Furthermore, values provide a top-down perspective for designing MASs which can be combined with traditional methods (e.g. norms, organizations) for lowering overall design complexity.

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Author information

Authors and Affiliations

  1. Utrecht Universiteit, The Netherlands

    Loïs Vanhée & Frank Dignum

  2. LIRMM, University of Montpellier II, France

    Loïs Vanhée & Jacques Ferber

Authors
  1. Loïs Vanhée
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  2. Frank Dignum
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  3. Jacques Ferber
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Editor information

Editors and Affiliations

  1. Department of Information and Computing Sciences, Utrecht University, Princetonplein 5, De Uithof, 3584 CC, Utrecht, The Netherlands

    Fabiano Dalpiaz

  2. Department of Informatics, Clausthal University of Technology, Julius-Albert-Str. 4, 38678,, Clausthal-Zellerfeld, Germany

    Jürgen Dix

  3. Department of Intelligent Systems, Faculty of Electrical Engineering, Delft University of Technology, Mekelweg 4, 2628 CD, Delft, The Netherlands

    M. Birna van Riemsdijk

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Vanhée, L., Dignum, F., Ferber, J. (2014). Robust Collaboration: Enriching Decisions with Abstract Preferences. In: Dalpiaz, F., Dix, J., van Riemsdijk, M.B. (eds) Engineering Multi-Agent Systems. EMAS 2014. Lecture Notes in Computer Science(), vol 8758. Springer, Cham. https://doi.org/10.1007/978-3-319-14484-9_21

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  • DOI: https://doi.org/10.1007/978-3-319-14484-9_21

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14483-2

  • Online ISBN: 978-3-319-14484-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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