Probabilistic representation of complexity.
type: Item
instance of: scholarly article
title: Probabilistic representation of complexity.
zbMATH Open document ID: 1063.91054
DOI: 10.1016/S0022-0531(03)00075-9
author: Nabil I. Al-Najjar
author: Ramon Casadesus-Masanell
author: Emre Ozdenoren
published in: Journal of Economic Theory
publication date: 2003-08-17T00:00:00Z
review text: A remarkable aspect of human behavior is individuals' ability to cope with complexity. The role of complexity in everyday life is almost self-evident: people engage in complex social and economic interactions where it is pointless to examine every possible contingency. While its importance and pervasiveness is beyond dispute, complexity is an elusive concept in a formally model. Difficulties arise from modeling complexity in a way that precludes systematic errors and arbitrage opportunities that undermine the equilibrium analysis. Here an agent's behavior is explained as a result of a coherent probabilistic model representing his attempt at identifying patterns or regularities, while at the same time recognizing that his model cannot explain everything. This paper proposes an approach that produces interesting cognitive limitations due to complexity, yet behavior is rational in the sense of being consistent with learning from data and displays no exploitable systematic errors.
Mathematics Subject Classification ID: 91B40
Mathematics Subject Classification ID: 91E10
Mathematics Subject Classification ID: 91A26
zbMATH DE Number: 1965053
zbMATH Keywords: labor market
zbMATH Keywords: cognitive psychology
zbMATH Keywords: cognitive uncertainty
reviewed by: Sergei Georgievich Zhuravlev
MaRDI profile type: Publication
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description: scientific article; zbMATH DE number 1965053