Proceedings of the workshop on Deception, Fraud, and Trust in Agent Societies held during the Autonomous Agents Conference: Trust in Cyber-societies, Integrating the Human and Artificial Perspectives
Formal Analysis of Models for the Dynamics of Trust Based on Experiences
MAAMAW '99 Proceedings of the 9th European Workshop on Modelling Autonomous Agents in a Multi-Agent World: MultiAgent System Engineering
Principles of Trust for MAS: Cognitive Anatomy, Social Importance, and Quantification
ICMAS '98 Proceedings of the 3rd International Conference on Multi Agent Systems
Trust in information sources as a source for trust: a fuzzy approach
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Trust Dynamics: How Trust Is Influenced by Direct Experiences and by Trust Itself
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Why a Cognitive Trustier Performs Better: Simulating Trust-Based Contract Nets
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
A Qualitative Bipolar Argumentative View of Trust
SUM '07 Proceedings of the 1st international conference on Scalable Uncertainty Management
Computing Confidence Values: Does Trust Dynamics Matter?
EPIA '09 Proceedings of the 14th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
A decentralized calendar system featuring sharing, trusting and negotiating
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
| Hi-index | 0.00 |
In this paper we propose a Bayesian dynamic trust model based on Castelfranchi and Falcone's works, thanks to which we can determine the agent's trust in another agent. Trust is not only a static mental state: it changes over time. Either some new observations are perceived and modify the trust level, or no observation is perceived and so trust is eroded. Our model takes into account these dynamic aspects by a Bayesian Kalman filter. We present, experiment and discuss our formalism compared with others models. The results obtained with our model are relevant and account for the particular dynamic aspects of trust.