Towards a Formalization of Trust

Thumbnail Image


Journal Title

Journal ISSN

Volume Title



This work focuses on the design and implementation of a new model of trust. The new model of trust is based on the formalizations of reputation, self-esteem, and similarity within an agent. Our previous work establishes the formalization of reputation within an information-sharing Multiagent System. The previous work claims that reputation cannot be universalized. This work universalizes reputation through the use of values within all Multiagent Systems. The following values are shown to be manifested within Multiagent Systems: responsibility, honesty, independence, obedience, ambition, helpfulness, capability, knowledgeability, and cost efficiency. Manifestations of these values result in a more universalized approach to formalizing reputation. Self-esteem is formalized as the reputation an agent has with itself. Lastly, similarity is formalized as the difference in the importance of the values previously mentioned. Combined, the weighted components of self-esteem, similarity, and reputation form a new model of trust. This new model of trust is examined within the context of an e-commerce framework. The multiagent system is comprised of buyers and sellers that wish to conduct business. Sellers can engage in untrustworthy business behavior at the buyer's expense. It is the job of the model to decide whether a selling agent is trustworthy enough to engage in business. The trust model is analyzed with respect to stability, scalability, accuracy in attaining e-commerce objectives, and general effectiveness in discouraging untrustworthy behavior. Based on the experiments, the model appears to be scalable dependent upon the agent population of buyers and sellers. It achieves its primary objective of discouraging untrustworthy behavior as measured through the acceleration of Gross Domestic Product growth over time. Within the simulator, a high degree of random outcomes is possible. Stability is used to examine the predictability of the model (on average) given a fixed set of given data about the simulations. Based on the simulations, the model appears to be quite stable.