Maxime Morge's Publications
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Combining statistics and arguments to compute trust
Paul-Amaury Matt, Maxime Morge, and Francesca Toni. Combining statistics and arguments to compute trust. In Proceedings of the ninth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'2010), pp. 209–210, International Foundation for Autonomous Agents and Multiagent Systems, 2010.
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Abstract
We propose a method for constructing Dempster-Shafer belief functions modeling the trust of a given agent (the evaluator) in another (the target) by combining statistical information concerning the past behaviour of the target and arguments concerning the targe's expected behaviour. These arguments are built from current and past contracts between evaluator and target. We prove that our method extends a standard computational method for trust that relies upon statistical information only. We observe experimentally that the two methods have identical predictive performance when the evaluator is highly "cautious", but our method gives a significant increase when the evaluator is not or is only moderately "cautious". Finally, we observe experimentally that target agents are more motivated to honour contracts when evaluated using our model of trust than when trust is computed on a purely statistical basis.
BibTeX
@InProceedings{matt10aamas,
author = {Paul-Amaury Matt and Maxime Morge and Francesca Toni},
title = {Combining statistics and arguments to compute trust},
booktitle = {Proceedings of the ninth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'2010)},
conference = {AAMAS'2010 -- Toronto (Canada) -- May 10-14, 2010},
pages = {209-210},
year = {2010},
editor = {Wiebe van der Hoek and Gal Kaminka and Yves Lespérance and Michael Luck and Sandip Sen},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
abstract= {We propose a method for constructing Dempster-Shafer
belief functions modeling the trust of a given agent (the
evaluator) in another (the target) by combining
statistical information concerning the past behaviour of
the target and arguments concerning the targe's expected
behaviour. These arguments are built from current and
past contracts between evaluator and target. We prove
that our method extends a standard computational method
for trust that relies upon statistical information
only. We observe experimentally that the two methods have
identical predictive performance when the evaluator is
highly "cautious", but our method gives a significant
increase when the evaluator is not or is only moderately
"cautious". Finally, we observe experimentally that
target agents are more motivated to honour contracts when
evaluated using our model of trust than when trust is
computed on a purely statistical basis.},
bib2html_pubtype = {International Conference},
bib2html_rescat = {MAS, Argumentation, Trust},
bib2html_funding = {ArguGRID}
}
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