2019-10-27 20:42:37 -04:00
|
|
|
import rltorch
|
|
|
|
|
|
|
|
sneaky_config = {}
|
2019-11-05 07:09:49 -05:00
|
|
|
sneaky_config['learning_rate'] = 1e-5
|
2019-10-27 20:42:37 -04:00
|
|
|
sneaky_config['target_sync_tau'] = 1e-3
|
|
|
|
sneaky_config['discount_rate'] = 0.99
|
2019-11-05 07:09:49 -05:00
|
|
|
sneaky_config['exploration_rate'] = rltorch.scheduler.ExponentialScheduler(initial_value = 1, end_value = 0.02, iterations = 10**5)
|
2019-10-27 20:42:37 -04:00
|
|
|
# Number of episodes for the computer to train the agent without the human seeing
|
2019-11-05 07:09:49 -05:00
|
|
|
sneaky_config['replay_skip'] = 29 # Gradient descent every second
|
|
|
|
sneaky_config['batch_size'] = 16 * (sneaky_config['replay_skip'] + 1) # Calculated based on memory constraints
|
|
|
|
sneaky_config['memory_size'] = 2000 # batch_size * 2 looks = 66 seconds of gameplay
|
|
|
|
# Number of episodes for the computer to train the agent without the human seeing
|
|
|
|
sneaky_config['num_sneaky_episodes'] = 10
|