Abstract
This paper discusses questions about communication of probabilistic knowledge in the light of current theories of agent communication. It will argue that there is a semantic gap between these theories and research areas related to probabilistic knowledge representation and communication, that creates very serious theoretical problems if agents that reason probabilistically try to use the communication framework provided by these theories. The paper proposes a new formal model, which generalizes current agent communication theories (at least the standard FIPA version of these theories) to handle probabilistic knowledge communication. We propose a new probabilistic logic as the basis for the model and new communication principles and communicative acts to support this kind of communication.
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Gluz, J.C., Vicari, R.M., Flores, C., Seixas, L. (2006). Formal Analysis of the Communication of Probabilistic Knowledge. In: Bramer, M. (eds) Artificial Intelligence in Theory and Practice. IFIP AI 2006. IFIP International Federation for Information Processing, vol 217. Springer, Boston, MA . https://doi.org/10.1007/978-0-387-34747-9_4
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DOI: https://doi.org/10.1007/978-0-387-34747-9_4
Publisher Name: Springer, Boston, MA
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