steffen/self-replicating-neural-networks
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Si11ium
2019-03-07 20:07:37 +01:00
parent 95c2ff4200
commit 7a76b1ba88
4 changed files with 35 additions and 41 deletions
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8
code/soup.py
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@ -59,7 +59,7 @@ class Soup:
particle.attack(other_particle)
description['action'] = 'attacking'
description['counterpart'] = other_particle.get_uid()
if prng() < self.params.get('train_other_rate'):
if prng() < self.params.get('train_other_rate') and hasattr(self, 'train_other'):
other_particle_id = int(prng() * len(self.particles))
other_particle = self.particles[other_particle_id]
particle.train_other(other_particle)
@ -150,7 +150,7 @@ class ParticleDecorator:
if __name__ == '__main__':
if False:
if True:
with SoupExperiment() as exp:
for run_id in range(1):
net_generator = lambda: WeightwiseNeuralNetwork(2, 2).with_keras_params(activation='linear').with_params()
@ -159,11 +159,11 @@ if __name__ == '__main__':
# net_generator = lambda: RecurrentNeuralNetwork(2, 2).with_keras_params(activation='linear').with_params()
soup = Soup(100, net_generator).with_params(remove_divergent=True, remove_zero=True)
soup.seed()
for _ in tqdm(range(100)):
for _ in tqdm(range(1000)):
soup.evolve()
exp.log(soup.count())
if True:
if False:
with SoupExperiment("soup") as exp:
for run_id in range(1):
net_generator = lambda: TrainingNeuralNetworkDecorator(WeightwiseNeuralNetwork(2, 2)).with_keras_params(