Market Mechanism Designs with Heterogeneous Trading Agents

Market mechanism design research is playing an important role in computational economics for resolving multi-agent allocation problems. A genetic algorithm was used to design auction mechanisms in order to automatically generate a desired market mechanism in agent based E-markets. In previous research, a hybrid market was studied, in which the probability that buyers rather than sellers are able to quote on a given time step, this probability was adapted by the GA which attempted to minimise Smith´s coefficient of convergence. However, in previous experiments, all trading agents involved are of the same type or have identical preferences. This assumption does not hold in real-world markets which are always populated with heterogeneous agents. In this paper, the research of using evolutionary computing methods for auction designs is extended by using heterogeneous trading agents