modeling trust using transactional, numerical units
In large electronic marketplaces populated by buying and selling agents, repeated transactions between traders may be rare. This makes it difficult for buying agents to judge the reliability of selling agents, discouraging participation in the market. A variety of systems have been proposed to help traders to find trustworthy partners; however, most proposed systems suffer from multiple vulnerabilities that might be exploited by unscrupulous parties. In this paper, we propose a new model, wherein abstract units are used to represent trust in much the same way that units of money represent value. In a manner similar to money, 'trunits' flow during transactions. A trader's trunit balance determines if they are trustworthy for a given transaction. Faithful execution of a transaction results in a larger trunit balance, permitting the trader to engage in more transactions in the future---a built-in economic incentive for honesty. We demonstrate that for a wide range of realistic market parameters, the Trunits mechanism ensures that honest sellers profit more than dishonest sellers. We also discuss how intrinsic properties of our model make it secure from many of the attacks to which other systems are vulnerable. In summary, we present our Trunits model as the basis for modeling trust in electronic marketplaces, useful as buying agents develop algorithms to intelligently choose trustworthy sellers for their business partners.
buying and selling e-commerce marketplaces trust and reputation multiagent systems