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Belief Revision and Argumentation Theory

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Argumentation in Artificial Intelligence

Belief revision is the process of changing beliefs to adapt the epistemic state of an agent to a new piece of information. The logical formalization of belief revision is a topic of research in philosophy, logic, and in computer science, in areas such as databases or artificial intelligence. On the other hand, argumentation is concerned primarily with the evaluation of claims based on premises in order to reach conclusions. Both provide basic and substantial techniques for the art of reasoning, as it is performed by human beings in everyday life situations and which goes far beyond logical deduction. Reasoning, in this sense, makes possible to deal successfully with problems in uncertain, dynamic environments and has been promoting the development of human societies.

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Acknowledgements

This research was funded by Consejo Nacional de Investigaciones Cientíificas y Técnicas (CONICET), Agencia Nacional de Promocion Científica y Tecnolóogica (ANPCyT), Universidad Nacional del Sur (UNS), Ministerio de Cienciay Tecnología (MinCyT) [Argentina] and Fundação para a Ciência e a Tecnologia (FCT) [Portugal].

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Authors and Affiliations

  1. CONICET (National Council of Technical and Scientific Research) – Department of ComputerScience and Engineering, Universidad Nacional del Sur, Bahía Blanca, Argentina

    Marcelo Alejandro Falappa

  2. Department of Computer Science, University of Dortmund, Dortmund, Germany

    Gabriele Kern-Isberner

  3. Department of Computer Science and Engineering, Universidad Nacional del Sur, Bahía Blanca, Argentina

    Guillermo Ricardo Simari

Authors
  1. Marcelo Alejandro Falappa
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  2. Gabriele Kern-Isberner
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  3. Guillermo Ricardo Simari
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Correspondence to Marcelo Alejandro Falappa .

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    Falappa, M.A., Kern-Isberner, G., Simari, G.R. (2009). Belief Revision and Argumentation Theory. In: Simari, G., Rahwan, I. (eds) Argumentation in Artificial Intelligence. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-98197-0_17

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    • DOI: https://doi.org/10.1007/978-0-387-98197-0_17

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