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Deliberation-Aware Responder in Multi-proposer Ultimatum Game

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Artificial Neural Networks and Machine Learning – ICANN 2016 (ICANN 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9886))

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Abstract

The article studies deliberation aspects by modelling a responder in multi-proposers ultimatum game (UG). Compared to the classical UG, deliberative multi-proposers UG suggests that at each round the responder selects the proposer to play with. Any change of the proposer (compared to the previous round) is penalised. The simulation results show that though switching of proposers incurred non-negligible deliberation costs, the economic profit of the deliberation-aware responder was significantly higher in multi-proposer UG compared to the classical UG.

This work was partially supported by the Grant Agency of the Czech Republic under the project GA16-09848S.

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Author information

Authors and Affiliations

  1. Department of Adaptive Systems, Institute of Information Theory and Automation, Czech Academy of Sciences, P.O. Box 18, 182 08, Prague, Czech Republic

    Marko Ruman, František Hůla, Miroslav Kárný & Tatiana V. Guy

Authors
  1. Marko Ruman
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  2. František Hůla
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  3. Miroslav Kárný
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  4. Tatiana V. Guy
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Corresponding author

Correspondence to Marko Ruman .

Editor information

Editors and Affiliations

  1. University of Lausanne, Lausanne, Switzerland

    Alessandro E.P. Villa

  2. University of Lausanne, Lausanne, Switzerland

    Paolo Masulli

  3. Universitat Politécnica de Catalunya, Terrrassa, Spain

    Antonio Javier Pons Rivero

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Ruman, M., Hůla, F., Kárný, M., Guy, T.V. (2016). Deliberation-Aware Responder in Multi-proposer Ultimatum Game. In: Villa, A., Masulli, P., Pons Rivero, A. (eds) Artificial Neural Networks and Machine Learning – ICANN 2016. ICANN 2016. Lecture Notes in Computer Science(), vol 9886. Springer, Cham. https://doi.org/10.1007/978-3-319-44778-0_27

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  • DOI: https://doi.org/10.1007/978-3-319-44778-0_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44777-3

  • Online ISBN: 978-3-319-44778-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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