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There are three different " symbol systems " available to social scientists: the familiar verbal argumentation and mathematics, but also a third way, computer simulation. Computer simulation, or computational modeling, involves representing a model as a computer program. The key question is: What tools can we use in building our models, if we follow the "(More)
In this paper we discuss strategies concerning the implementation of an agent-based simulation of complex phenomena. The model we consider accounts for population decomposition and interaction in industrial districts. The approach we follow is twofold: on one hand, we implement progressively more complex models using different approaches (vertical multiple(More)
With SUM, a Surprising (Un)realistic Market, we are dealing with the micro-foundations of a stock market. We avoid any artificially simplified solution about price formation, such as to employ an auctioneer to clear the market; on the contrary, our model produces time series of prices continuously evolving, transaction by transaction. The core of the model(More)
This paper concerns agent based experiments in the field of negotiation and exchange simulation. A computer simulation environment is built, showing the emergence of chaotic price sequences in a simple model of interacting consumers and vendors, both equipped with minimal rules. " Swarm " is the framework of the model (www.santafe.edu/projects/swarm), a(More)
In computer simulation models based upon agents, what is the degree of sophistication that we have to put into the agents? Should we provide them or not with a " mind " ? The answer ranges from Axelrod's simplicity principle to the use of full BDI (Beliefs, Intentions, Desires) cognitive agents. To discuss the subject we introduce here three models: one(More)