{
  "id": "cond-mat/9906058",
  "version": "v3",
  "published": "1999-06-04T08:55:19.000Z",
  "updated": "2000-03-03T17:16:51.000Z",
  "title": "Dynamics of Interacting Neural Networks",
  "authors": [
    "W. Kinzel",
    "R. Metzler",
    "I. Kanter"
  ],
  "comment": "9 pages, 3 figures; typos corrected, content reorganized",
  "categories": [
    "cond-mat.dis-nn"
  ],
  "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.",
  "revisions": [
    {
      "version": "v3",
      "updated": "2000-03-03T17:16:51.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "interacting neural networks",
      "interacting perceptrons",
      "symmetry breaking phase transition",
      "system runs",
      "higher symmetry"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 9,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "1999cond.mat..6058K"
    }
  }
}