Dynamics of Interacting Neural Networks

W. Kinzel, R. Metzler, I. Kanter

Published 1999-06-04, updated 2000-03-03Version 3

The dynamics of interacting perceptrons is solved analytically. For a directed flow of information the system runs into a state which has a higher symmetry than the topology of the model. A symmetry breaking phase transition is found with increasing learning rate. In addition it is shown that a system of interacting perceptrons which is trained on the history of its minority decisions develops a good strategy for the problem of adaptive competition known as the Bar Problem or Minority Game.