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Article Dans Une Revue Physica A: Statistical Mechanics and its Applications Année : 2013

More memory under evolutionary learning may lead to chaos

Résumé

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.

Dates et versions

hal-04575563 , version 1 (15-05-2024)

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Cees Diks, Cars Hommes, Paolo Zeppini. More memory under evolutionary learning may lead to chaos. Physica A: Statistical Mechanics and its Applications, 2013, 392 (4), pp.808-812. ⟨10.1016/j.physa.2012.10.045⟩. ⟨hal-04575563⟩
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