Market Mechanism Designs with Heterogeneous Trading Agents

Abstract

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