The New Evolutionary Computational Paradigm of Complex Adaptive Systems: Challenges and Prospects for Economics and Finance
AbstractThe new evolutionary computational paradigm of market systems views these as complex adaptive systems. The major premise of 18th century classical political economy was that order in market systems is spontaneous or emergent, in that it is the result of 'human action but not of human design'. This early observation on the disjunction between system wide outcomes and capabilities of micro level rational calculation marks the provenance of modern evolutionary thought. However, it will take a powerful confluence of two 20th century epochal developments for the new evolutionary computational paradigm to rise to the challenge of providing long awaited explanations of what has remained anomalies or outside the ambit of traditional economic analysis. The first of these is the G�del-Turing-Post results on incompleteness and algorithmically unsolvable problems that delimit formalist calculation or deductive methods. The second is the Anderson-Holland-Arthur heterogeneous adaptive agent theory and models for inductive search, emergence and self-organized criticality which can crucially show and explicitly study the processes underpinning the emergence of ordered complexity. Multi-agent model simulation of asset price formation and the innovation based structure changing dynamics of capitalist growth are singled out for analysis of this disjunction between non-anticipating global outcomes and computational micro rationality.
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Bibliographic InfoPaper provided by University of Essex, Department of Economics in its series Economics Discussion Papers with number 532.
Date of creation: 2001
Date of revision:
Postal: Discussion Papers Administrator, Department of Economics, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, U.K.
This paper has been announced in the following NEP Reports:
- NEP-ALL-2002-04-15 (All new papers)
- NEP-CMP-2002-04-15 (Computational Economics)
- NEP-MIC-2002-04-15 (Microeconomics)
- NEP-PKE-2002-04-15 (Post Keynesian Economics)
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- Sheri Markose & Amadeo Alentorn & Andreas Krause, 2004. "Dynamic Learning, Herding and Guru Effects in Networks," Economics Discussion Papers 582, University of Essex, Department of Economics.
- Sheri M. Markose, 2005.
"Computability and Evolutionary Complexity: Markets as Complex Adaptive Systems (CAS),"
Royal Economic Society, vol. 115(504), pages F159-F192, 06.
- Sheri M. Markose, 2004. "Computability and Evolutionary Complexity: Markets As Complex Adaptive Systems (CAS)," Economics Discussion Papers 574, University of Essex, Department of Economics.
- Sheri M. Markose, 2004. "Novelty And Surprises In Complex Adaptive System (CAS) Dynamics: A Computational Theory of Actor Innovation," Economics Discussion Papers 575, University of Essex, Department of Economics.
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