On the evolution of interaction rules in a canonical auction market with simple bidding agents

Auction markets have been continually attracting attention in the field of economics due to their interesting properties as trading institutions. The recent boom of electronic markets over the Internet has also sparked related research in the field of artificial intelligence (AI). The main aspects investigated concerning electronic markets are the construction of automated negotiating agents, and the design of mechanisms and protocol rules to coordinate their interaction. In this paper, the construction of rules, by a genetic algorithm, to coordinate the bidders interaction in a canonical auction market is investigated. Auction rules have been deeply investigated in scenarios with human actors, where commonsense protocols naturally prevail, restricting the possibilities of using idiosyncratic interaction procedures. By means of computational experiments, we show that in a hypothetical situation where the bidders follow very simple strategies, non-conventional auction rules can perform better than conventional protocols.