The emergence of trust in multi-agent bidding: a computational approach

We experiment conditions for the emergence of trust in a multi-agent bidding setting using a computational approach. This is a follow up of our study on multi-agent bidding and contracting for nonstorable goods. In this framework there is a long-term contract market as well as a back-stop spot market. Seller agents bid into an electronic bulletin board their contract offers in terms of price and capacity, while buyer agents decide how much to contract with the sellers and how much to shop from the spot market. The goal is the following: First, to investigate if agents using reinforcement learning (nonmyopic bidding) can discover good and effective bidding, auction and contracting strategies when playing repeated nonlinear games where there does not exist any equilibrium; Second, to explore the emergence of trust in the sense of what kind of mechanisms induce cooperation in the above repeated nonlinear game.