Abstract
There are many possible ways of modelling economic agents. These traditionally fall into one of two camps, dating from Simon’s distinction between substantive and procedural rationality: this is often characterised as those with bounded rationality and those with no such bounds (although this is not strictly correct, Moss & Sent forthcoming). Although the latter type is more analytically tractable we are interested in the former type.
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References
Akiyama, E. and K. Kaneko: 1996, ‘Evolution of Cooperation, Differentiation, Complexity, and Diversity in an Iterated Three-person Game’. Artificial Life 2, 293–304.
Angeline, P. and K. E. Kinnear: 1996, Advances in Genetic Programming, Vol.2. Cambridge, MA: MIT Press.
Arifovic, J.: 1994, ‘Genetic Algorithm Learning and the Cobweb Model’. Journal of Economic Dynamics and Control 18, 3–28.
Arthur, B.: 1994, ‘Inductive Reasoning and Bounded Rationality’. American Economic Association Papers 84, 406–411.
Axelrod, R.: 1984, The Evolution of Cooperation. New York: Basic Books.
Dosi, G., L. Marengo, A. Bassanini & M. Valente: forthcoming, ‘Norms as Emergent Properties of Adaptive Learning’. Journal of Evolutionary Economics,.
Edmonds, B.: 1998a, ‘Meta-Genetic Programming: co-evolving the genetic operators’. CPM Report 98–32, MMU, Manchester, UK. (http://www.cpm.mmu.ac.uk/cpmrep32.html)
Edmonds, B.: 1998b, ‘Modelling Socially Intelligent Agents’. Applied Artificial Intelligence 12, 677–699.
Elman, J.L.: 1993, ‘Learning and Development in Neural Networks - The Importance of Starting Small’. Cognition 48, 71–99.
Gaylard, H.: 1996, ‘A Cognitive Approach to Modelling Structural Change’. CPM Report 96–20, MMU, Manchester, UK.
Holland, J. H.: 1992, Adaptation in Natural and Artificial Systems, 2nd Ed.. Cambridge, MA: MIT Press.
Kaneko, K.: 1990, ‘Globally Coupled Chaos Violates the Law of Large Numbers but not the Central Limit Theorem’. Physics Review Letters 65, 1391–1394.
Kinnear, K. E. (ed.): 1994, Advances in Genetic Programming. Cambridge, MA: MIT Press.
Koza, J. R.: 1992, Genetic Programming: On the Programming of Computers by Means of Natural Selection. Cambridge, MA: MIT Press.
Montana, D. J.: 1995, ‘Strongly Typed Genetic Programming’. Evolutionary Computation 3, 199–230.
Moss, S. J. and B. Edmonds: 1998, ‘Modelling Economic Learning as Modelling’. Cybernetics and Systems 29, 5–37.
Moss, S. J., H. Gaylard, S. Wallis, and B. Edmonds: 1998, ‘SDML: A Multi-Agent Language for Organizational Modelling’. Computational and Mathematical Organization Theory 4, 43–69.
Moss, S. and Sent, E-M.: 1998, ‘Boundedly versus Procedurally Rational Expectations’. In: Hallet, H and McAdam, P. (eds.), New Directions in Macro Economic Modelling,: Kluwer, pp..
Palmer, R.G. et. al.: 1994, ‘Artificial Economic Life - A simple model of a stockmarket’. Physica D 75,264–274.
Penrose, E.: 1972, The Growth of the Firm. Oxford: Blackwell.
Prügel-Bennett, A. and J. L. Shapiro: 1994, ‘An Analysis of Genetic Algorithms Using Statistical Mechanics’. Physical Review Letters 72, 1305–1309.
Vriend, N.J.: 1995, ‘Self-organization of markets: an example of a computational approach’. Computational Economics 8, 205–232.
Zambrano, E.: 1997, ‘The Revelation Principle of Bounded Rationality’. Sante Fe working paper 97–06–060, New Mexico, USA.
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Edmonds, B. (1999). Modelling Bounded Rationality in Agent-Based Simulations Using the Evolution of Mental Models. In: Brenner, T. (eds) Computational Techniques for Modelling Learning in Economics. Advances in Computational Economics, vol 11. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5029-7_13
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DOI: https://doi.org/10.1007/978-1-4615-5029-7_13
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