19、ES-HyperNEAT、视网膜问题与协同进化探索

ES-HyperNEAT、视网膜问题与协同进化探索

1. ES-HyperNEAT实验流程

在进行视网膜问题的实验时，首先需要对构建的探测器人工神经网络（ANN）进行评估，具体代码如下：

outputs = net.NumOutputs()
hidden = len(net.neurons) - net.NumInputs() - net.NumOutputs()
print("\n\tinputs: %d, outputs: %d, hidden: %d" % (inputs, outputs, hidden))

# Test against random retina configuration
l_index = random.randint(0, 15)
r_index = random.randint(0, 15)
left = rt_environment.visual_objects[l_index]
right = rt_environment.visual_objects[r_index]
err, outputs = rt_environment._evaluate(net, left, right, 3)
print("Test evaluation error: %f" % err)
print("Left flag: %f, pattern: %s" % (outputs[0], left))
print("Right flag: %f, pattern: %s" % (outputs[1], right))

# Test against all visual objects
fitness, avg_err