Self-organization of markets: an example of a computational approach
Computational Economics - Special issue: genetic algorithms
Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
A Behavioural Learning Approach to the Dynamics ofPrices
Computational Economics - Special issue: Evolutionary processes in economics
Aspiration-based and reciprocity-based rules in learning dynamics for symmetric normal-form games
Journal of Mathematical Psychology
Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics (Handbook of Computational Economics)
A computational approach to modeling commodity markets
Computational Economics
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In the mainstream top-down approach, money is neutral except with special assumptions. Intending to make money "essential", random-matching models introduced decentralisation by considering pair-wise transactions. Nevertheless, in both cases top-level equilibrium constrains agents' behaviour. Instead, here we use a bottom-up approach. In a competitive market, decentralised autonomous agents meet and exchange a commodity for money. Their decisions use minimal information. They are triggered by simple rules founded on a "satisficing" procedure and on a random decision process that simulates bounded rationality. The conclusions are, first, that non-monetary costs are essential to avoid collapse of the economy. Second, mainly "price setters" who are adequately satisfied achieve equilibrium protecting themselves by evolving advantages to avoid competition that is too tough. Third, and the most important conclusion is that money ceases to be neutral as soon as competition arises between individual firms.