Managing Knowledge in Agent-based Models: Theoretical and Methodological Issues

Ferraris Gianluigi () and Magda Fontana

Department of Economics and Statistics Cognetti de Martiis. Working Papers from University of Turin

Abstract: The paper proposes an experimental setup to compare different representations of artificial adaptive agents (genetic algorithms, artificial neural networks, and classifier systems) and suggests some criteria to assess equivalence and robustness of performance. In economie theory, the use of artificial adaptive agents as substitutes for the homo oeconomicus raises important methodological issues. While the reductionist approach grounded on Olympic rationality offers full rationality as the unique reference point for problem solving, weaker notions of rationality generate a variety of processes and outcomes of decision-making. The paper gives some suggestions on sensitivity of the behaviour of agents to the algorithmic choice and to the codification of knowledge. Preliminary results show that in an iterated prisoner's dilemma interesting patterns of behaviour (such as strategies that perform better than the tit-for-tat) emerge.

Pages: 26 pages
Date: 2006-01
New Economics Papers: this item is included in nep-knm
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