Abstract
This paper introduces a formal method to aggregate over basic beliefs, in order to deduce aggregated or complex beliefs as often used in applications. Complex beliefs can represent several things, such as a belief about a period in which other beliefs held or the minimal or maximal certainty with which a belief held. As such they contain richer information than the basic beliefs they are aggregated from and can be used to optimize an agent’s search through its memory and its reasoning processes. The developed method can also aggregate over aggregated beliefs, hence nested aggregations are possible. An implementation in Prolog demonstrates its operationality.
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Heuvelink, A., Klein, M.C.A., Treur, J. (2008). A Formal Approach to Aggregated Belief Formation. In: Klusch, M., Pěchouček, M., Polleres, A. (eds) Cooperative Information Agents XII. CIA 2008. Lecture Notes in Computer Science(), vol 5180. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85834-8_8
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DOI: https://doi.org/10.1007/978-3-540-85834-8_8
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