Affiliation:
1. Missouri University of Science and Technology, USA
Abstract
As the study of agent-based computational economics and finance grows, so does the need for appropriate techniques for the modeling of complex dynamic systems and the intelligence of the constructive agent. These methods are important where the classic equilibrium analytics fail to provide sufficiently satisfactory understanding. In particular, one area of computational intelligence, Approximate Dynamic Programming, holds much promise for applications in this field and demonstrate the capacity for artificial Higher Order Neural Networks to add value in the social sciences and business. This chapter provides an overview of this area, introduces the relevant agent-based computational modeling systems, and suggests practical methods for their incorporation into the current research. A novel application of HONN to ADP specifically for the purpose of studying agent-based financial systems is presented.
Reference71 articles.
1. Adaptive critic designs for discrete-time zero-sum games with application to H-infinity control.;A.Al-Timini;IEEE Transactions on Systems, Man, and Cybernetics,2007
2. Genetic algorithm learning and the cobweb model
3. The Behavior of the Exchange Rate in the Genetic Algorithm and Experimental Economies
4. Arrow, K. J. (1958). Historical Background. In Arrow, K., Karlin, S., & Scarf, H., Eds. Studies in the Mathematical Theory of Inventory and Production. Stanford University Press. Stanford, CA.
5. Inductive reasoning and bounded rationality;W. B.Arthur;The American Economic Review,1994