Abstract
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.
Original language | English |
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Pages (from-to) | L141-L147 |
Journal | Journal of Physics A: Mathematical and General |
Volume | 33 |
Issue number | 14 |
DOIs | |
State | Published - 14 Apr 2000 |