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Four Ways to Evaluate Arguments According to Agent Engagement

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Brain Informatics and Health (BIH 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9250))

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Abstract

In this paper we are interested in the computational and formal analysis of the persuasive impact that an argument can have on a human. We present a preliminary account of the listener mental process (representation and reasoning mechanisms of the dual process cognitive model) as well as her engagement based on the ELM model. This engagement determines the reasoning process that the agent will adopt in order to evaluate and incorporate the uttered argument.

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Author information

Authors and Affiliations

  1. INRA, Montpellier, France

    Pierre Bisquert

  2. University of Montpellier, Montpellier, France

    Madalina Croitoru

  3. IRIT, Toulouse, France

    Florence Dupin de Saint-Cyr

Authors
  1. Pierre Bisquert
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  2. Madalina Croitoru
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  3. Florence Dupin de Saint-Cyr
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Corresponding author

Correspondence to Pierre Bisquert .

Editor information

Editors and Affiliations

  1. Imperial College London , Data Science Institute, London, United Kingdom

    Yike Guo

  2. Institute of Cognitive Neuroscience, University College London, London, United Kingdom

    Karl Friston

  3. Imperial College London, London, United Kingdom

    Faisal Aldo

  4. Campus Biotech, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland

    Sean Hill

  5. Allen Institute for Brain Science, Seattle, USA

    Hanchuan Peng

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© 2015 Springer International Publishing Switzerland

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Bisquert, P., Croitoru, M., Dupin de Saint-Cyr, F. (2015). Four Ways to Evaluate Arguments According to Agent Engagement. In: Guo, Y., Friston, K., Aldo, F., Hill, S., Peng, H. (eds) Brain Informatics and Health. BIH 2015. Lecture Notes in Computer Science(), vol 9250. Springer, Cham. https://doi.org/10.1007/978-3-319-23344-4_43

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  • DOI: https://doi.org/10.1007/978-3-319-23344-4_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23343-7

  • Online ISBN: 978-3-319-23344-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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