Abstract
In distributed artificial intelligence systems it is important that the constituent intelligent systems communicate. This may be a problem if the systems use different methods to represent uncertain information. This paper presents a method that enables systems that use different uncertainty handling formalisms to qualitatively integrate their uncertain information, and argues that this makes it possible for distributed intelligent systems to achieve tasks that would otherwise be beyond them.
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© 1993 Springer-Verlag Berlin Heidelberg
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Parsons, S., Saffiotti, A. (1993). Integrating uncertainty handling formalisms in distributed artificial intelligence. In: Clarke, M., Kruse, R., Moral, S. (eds) Symbolic and Quantitative Approaches to Reasoning and Uncertainty. ECSQARU 1993. Lecture Notes in Computer Science, vol 747. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0028214
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DOI: https://doi.org/10.1007/BFb0028214
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-57395-1
Online ISBN: 978-3-540-48130-0
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