TY - JOUR
T1 - More memory under evolutionary learning may lead to chaos
AU - Diks, Cees
AU - Hommes, Cars
AU - Zeppini, Paolo
PY - 2013/2/15
Y1 - 2013/2/15
N2 - 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.
AB - 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.
UR - http://dx.doi.org/10.1016/j.physa.2012.10.045
U2 - 10.1016/j.physa.2012.10.045
DO - 10.1016/j.physa.2012.10.045
M3 - Article
SN - 0378-4371
VL - 392
SP - 808
EP - 812
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
IS - 4
ER -