{
  "input": 1,
  "target": 1,
  "activation": "sigmoid",
  "output": "v0*h0+v1*h1+c",
  "loss": "0.5*(output-target)^2",
  "symmetric_initial": {
    "w": [
      0.2,
      0.2
    ],
    "b": [
      0,
      0
    ],
    "v": [
      0.5,
      0.5
    ],
    "c": 0
  },
  "asymmetric_change": "only w1=-0.2",
  "optimizer": "simultaneous deterministic gradient descent",
  "learning_rate": 0.1,
  "steps": 3,
  "dropout": false,
  "data_fictional": true
}