Learning to speculate: Experiments with artificial and real agents

This paper employs an artificial agent-based computational approach to unde rstanding and designing laboratory environments in which to lest Kiyotaki a nd Wright's search model of money. The behavioral rules of the artificial a gents are modeled on the basis of prior evidence from human subject experim ents. Simulations of the artificial agent-based model are conducted in two new versions of the Kiyotaki-Wright environment and yield some testable pre dictions. These predictions are examined using data from new, human subject experiments. The results are encouraging and suggest that artificial agent -based modeling may be a useful device for both understanding and designing human subject experiments. (C) 2001 Elsevier Science B.V. Ail rights reser ved. JEL classification: D83; C73; C90; E40.