The Agent-Based Double Auction Markets: 15 Years On [chapter]

Shu-Heng Chen, Chung-Ching Tai
2010 Simulating Interacting Agents and Social Phenomena  
Novelties discovering as a source of constant change is the essence of economics. However, most economic models do not have the kind of noveltiesdiscovering agents required for constant changes. This silence was broken by Andrews and Prager 15 years ago when they placed GP (genetic programming)-driven agents in the double auction market. The work was, however, neither economically well interpreted nor complete; hence the silence remains in economics. In this article, we revisit their model and
more » ... ystematically conduct a series of simulations to better document the results. Our simulations show that human-written programs, including some reputable ones, are eventually outperformed by GP. The significance of this finding is not that GP is alchemy. Instead, it shows that novelties-discovering agents can be introduced into economic models, and their appearance inevitably presents threats to other agents who then have to react accordingly. Hence, a potentially indefinite cycle of change is triggered. 1 See [22] , p. 28-30. 2 Genetic algorithms and learning classifier systems can be other alternatives. However, to the best of our knowledge, most agent-based economic applications of genetic algorithms do not manifest this capability, and, for some reason not exactly known, there are almost no agent-based economic applications of learning classifier systems. 3 The reason why we choose the agent-based double auction market as the main pursuit of this paper is because this is one of the few economic models in which human agents, programmed agents and autonomous agents have been involved. See Section 2 for the details.
doi:10.1007/978-4-431-99781-8_9 dblp:conf/wcss/ChenT08 fatcat:t55rmrkvabd6ncfzh6lkhec6ki