publication . Conference object . 2015

A Computational Model of Trust Based on Message Content and Source

Da Costa Pereira, Célia; Tettamanzi, Andrea G. B.; Villata, Serena;
Open Access English
  • Published: 04 May 2015
  • Publisher: HAL CCSD
International audience; We propose a general possibilistic framework to determine the a-gent's trust degree in a source, starting from the content of the messages such source provides and based on the beliefs of the agent about the capability of the source to provide " useful information ". The result is a framework with unique characteristics, which combines experience-, reputation-, content-, and category-based models of trust in one coherent computational model.
free text keywords: Trust, Distrust, BDI Agents, Argumentation Theory, Goals, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.11: Distributed Artificial Intelligence/I.2.11.3: Multiagent systems, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Download from
Hyper Article en Ligne
Conference object . 2015

MIT Press, 2008. [1] P. Besnard and A. Hunter. Elements of Argumentation. The [2] C. Castelfranchi and R. Falcone. Social trust: A cognitive approach. In C. Castelfranchi and Y.-H. Tan, editors, Trust and Deception in Virtual Societies, pages 55-90. Springer, 2001. [3] C. da Costa Pereira, A. Tettamanzi, and S. Villata. Changing one's mind: Erase or rewind? In IJCAI, pages 164-171, 2011. [4] D. Dubois and H. Prade. Possibility Theory. Plenum, New [5] M. Mas, M. Monserrat, J. Torrens, and E. Trillas. A survey on York, 1988.

fuzzy implication functions. Trans. Fuz Sys., 15(6):1107-1121, 2007. [6] D. H. McKnight and N. L. Chervany. Trust and distrust definitions: One bite at a time. In Trust in Cyber-societies, volume 2246 of Lecture Notes in Computer Science, pages 27-4. Springer, 2000.

Powered by OpenAIRE Research Graph
Any information missing or wrong?Report an Issue