More memory under evolutionary learning may lead to chaos
Cees Diks,
Cars Hommes and
Paolo Zeppini
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Cees Diks: CeNDEF - Center for Nonlinear Dynamics in Economics and Finance - UvA - University of Amsterdam [Amsterdam] = Universiteit van Amsterdam
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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.
Keywords: Heterogeneous agents; Imitation; Innovation; Memory; Stability (search for similar items in EconPapers)
Date: 2013-02
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Published in Physica A: Statistical Mechanics and its Applications, 2013, 392 (4), pp.808-812. ⟨10.1016/j.physa.2012.10.045⟩
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Journal Article: More memory under evolutionary learning may lead to chaos (2013) 
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04575563
DOI: 10.1016/j.physa.2012.10.045
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