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An Emotional Multi-personality Architecture for Intelligent Conversational Agents

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Transactions on Computational Collective Intelligence XXVIII

Part of the book series: Lecture Notes in Computer Science ((TCCI,volume 10780))

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Abstract

Personal assistants and chatterbots represent an historical and growing application field in artificial intelligence. This paper presents a novel architecture to the problem of humanizing conversational agents by designing believable and unforgettable characters who exhibit various salient emotions in the flow of conversations. The proposed architecture is based on a multi-personality approach where each agent implements a facet of its identity, each one with its own pattern of perceiving and interacting with the user. In order to select an appropriate response from all the candidates, we use an emotion-based selection algorithm. Our first experiments show that a conversational multi-personality character with emotion selection performs better in terms of user engagement than a neutral mono-personality one.

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Author information

Authors and Affiliations

  1. Léonard de Vinci Pôle Universitaire, Research Center, Paris – La Défense, France

    Jean-Claude Heudin

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  1. Jean-Claude Heudin
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Correspondence to Jean-Claude Heudin .

Editor information

Editors and Affiliations

  1. Wrocław University of Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Swinburne University of Technology, Hawthorn, Victoria, Australia

    Ryszard Kowalczyk

  3. Leiden University, Leiden, The Netherlands

    Jaap van den Herik

  4. Universidade do Porto, Porto, Portugal

    Ana Paula Rocha

  5. INSTICC, Polytechnic Institute of Setúbal, Setubal, Portugal

    Joaquim Filipe

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Heudin, JC. (2018). An Emotional Multi-personality Architecture for Intelligent Conversational Agents. In: Nguyen, N., Kowalczyk, R., van den Herik, J., Rocha, A., Filipe, J. (eds) Transactions on Computational Collective Intelligence XXVIII. Lecture Notes in Computer Science(), vol 10780. Springer, Cham. https://doi.org/10.1007/978-3-319-78301-7_7

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  • DOI: https://doi.org/10.1007/978-3-319-78301-7_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-78300-0

  • Online ISBN: 978-3-319-78301-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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