Code used to obtain these results can be found at the url https://github.com/NervanaSystems/simple_dqn, commit 31a92a9.
This code runs with Neon commit 344372b. Training and test scripts are included in
Note that for training, the screen width and screen height must be specified as (40, 52).
Default training paramters are used as set in
src/main.py. This model was trained for 77 epochs which will take roughly 15 hours to train on a Titan X GPU.
learning_rate=0.00025: Learning rate
discount_rate=0.99: Discount rate for future rewards
batch_size=32: Batch size for neural network
optimizer=rmsprop: Network optimization algorithm
decay_rate=0.95: Decay rate for RMSProp algorithm
clip_error=1: Clip error term in update.
train_steps=250000: How many training steps per epoch
epochs=77: How many epochs to run