|
If you are seeing this message, you may be experiencing temporary network problems. Please wait a few minutes and refresh the page. If the problem persists, you may wish to report it to your local Network Manager.
It is also possible that your web browser is not configured or not able to display style sheets. In this case, although the visual presentation will be degraded, the site should continue to be functional. We recommend using the latest version of Microsoft or Mozilla web browser to help minimise these problems.
Wiley InterScience | |||
  The Economic JournalVolume 115 Issue 504, Pages F159 - F192 Published Online: 17 Jun 2005 Journal compilation © 2010 by the Royal Economic Society (Registered Charity No. 231508) Published on behalf of the Royal Economic Society
Abstract | References | Full Text: HTML, PDF (Size: 425K) | Related Articles | Citation Tracking  Computability and Evolutionary Complexity: Markets as Complex Adaptive Systems (CAS)* * I am grateful for discussions over the years with Ken Binmore, Steve Spear, Vela Velupillai and for an important meeting and email correspondence with Herbert Simon. I thank John Sutton for letting me use his data in Section 3. Comments from two anonymous referees have improved many aspects of this paper and that of the Feature as a whole. Recent discussions with Thomas Lux, Jasmina Arifovic, Edward Tsang, Eliot Maenner, Shyam Sunder, Bernhard von Stengel and the Feature contributors Robert Axtell, Steven Durlauf and Arthur Robson have helped produce a coherent whole. I particularly appreciate Steve Machin's encouragement and patience in the process of bringing this Feature to fruition. Copyright 2005 Royal Economic Society ABSTRACTFew will argue that the epi-phenomena of biological systems and socio-economic systems are anything but complex. The purpose of this Feature is to examine critically and contribute to the burgeoning multi-disciplinary literature on markets as complex adaptive systems (CAS). The new sciences of complexity, the principles of self-organisation and emergence along with the methods of evolutionary computation and artificially intelligent agent models have been developed in a multi-disciplinary fashion. The cognoscenti here consider that complex systems whether natural or artificial, physical, biological or socio-economic can be characterised by a unifying set of principles. Further, it is held that these principles mark a paradigm shift from earlier ways of viewing such phenomenon. | 
|
