The new evolutionary computational paradigm of complex adaptive systems. Challenges and prospects for economics and finance

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@TechReport{markoso:2001:CFtr,

• author = "Sheri M. Markose",
• title = "The new evolutionary computational paradigm of complex adaptive systems. Challenges and prospects for economics and finance",
• institution = "Department of Economics, University of Essex",
• year = "2001",
• type = "Discussion paper series",
• number = "532",
• month = jul,
• note = "See Kluwer series on Computational Finance, Jan 2002",
• email = "scher@essex.ac.uk",
• keywords = "genetic algorithms, genetic programming",
• URL = "http://www.essex.ac.uk/economics/discussion-papers/papers-text/dp532.pdf",
• size = "53 pages",
• abstract = "The 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 Godel-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-organised 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.",
• notes = "See \cite{Markose:2002:gagpcf}",

}

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