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Learning to Trust

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Book cover Trust in Cyber-societies

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2246))

Abstract

Evolutionary game-theory is a powerful tool to investigate the development of complex relations between individuals such as the emergence of cooperation and trust. But the propagation of genes is an unrealistic assumption when it comes to model fast-changing social interactions.We show how a transition frome volutionary game-theory to learning can be made. Specifically, we show how cooperation and trust can develop together through social interactions and a suited learning mechanism.

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Author information

Authors and Affiliations

  1. Artificial Intelligence Laboratory, Vrije Universiteit Brussel, Pleinlaan 2, 10G725, 1050, Brussels, Belgium

    Andreas Birk

Authors
  1. Andreas Birk
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Editor information

Editors and Affiliations

  1. Group of Artificial Intelligence, Cognitive and Interacting Modelling, National Research Council, Institute for Cognitive Science and Technology, Viale Marx 15, 00137, Rome, Italy

    Rino Falcone

  2. Department of Computer Science, North Carolina State University, 940 Main Campus Drive, Suite 110, 27606, Raleigh, NC, USA

    Munindar Singh

  3. Department of Economics and Business Administration, Free University Amsterdam, De Boelelaan 1105, 1081, HV Amsterdam, The Netherlands

    Yao-Hua Tan

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© 2001 Springer-Verlag Berlin Heidelberg

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Birk, A. (2001). Learning to Trust. In: Falcone, R., Singh, M., Tan, YH. (eds) Trust in Cyber-societies. Lecture Notes in Computer Science(), vol 2246. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45547-7_8

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  • DOI: https://doi.org/10.1007/3-540-45547-7_8

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43069-8

  • Online ISBN: 978-3-540-45547-9

  • eBook Packages: Springer Book Archive

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