More memory under evolutionary learning may lead to chaos
Abstract
We show that an increase of memory of past strategy performance in a simple agent-based innovation model, with agents switching between costly innovation and cheap imitation, can be quantitatively stabilising while at the same time qualitatively destabilising. As memory in the fitness measure increases, the amplitude of price fluctuations decreases, but at the same time a bifurcation route to chaos may arise. The core mechanism leading to the chaotic behaviour in this model with strategy switching is that the map obtained for the system with memory is a convex combination of an increasing linear function and a decreasing non-linear function.Download Info
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Bibliographic Info
Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.
Volume (Year): 392 (2013)
Issue (Month): 4 ()
Pages: 808-812
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Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/
Related research
Keywords: Heterogeneous agent models; Imitation; Innovation; Memory; Stability;References
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