About the convergence and overfit

[marooncn]

Hi, thanks for your job and I rewrite it using Keras in the attitude of learning. And I use your recommended hyper-parameters but when I run my program it's apt to overfit. Later on, I change the hyper-parameters , add BN and explicit initialization function of each layer. But it's still overfitting and the car runs 700 steps at the best time but still can't go through the all track. I have spent more than two weeks to tune it. I'm so confused of the tuning, why the same hyper-parameters can't achieve the same result? Why the network is so apt to overfit?
For convenience, I update my programmer
imitationLearning.py
Can you give me some idea?
Than you in advance.