I’m working with ML-Agents and to start I can’t get the behavior to use the script I applied to my agent. It mentions that it can’t find an agent with this name. I can’t figure out how to create that actual behavior so I thought I’d change the default settings in settings.py to have an increased max_steps. This worked until yesterday but since yesterday it will just use 500000 no matter if I change it. Does someone know how to create a new behavior so that I can create one per agent or know how I can change the default max_steps.
Any help with how to debug this would also be greatly appreciated!
In the behaviour paramters there is the max steps for one episode; but you mean the maxsteps for the agent training:
just when starting training: mlagents-learn path\to\myconfig.yaml give your yaml as a parameter
“MyAgent” has to be set also in your Behavour script as the behaviour name
example for a .yaml
behaviors:
MyAgent:
trainer_type: ppo
hyperparameters:
batch_size: 2048
buffer_size: 20480
learning_rate: 0.0003
beta: 0.005
epsilon: 0.2
lambd: 0.95
num_epoch: 3
learning_rate_schedule: linear
network_settings:
normalize: true
hidden_units: 512
num_layers: 3
vis_encode_type: simple
memory:
sequence_length: 128
memory_size: 256
reward_signals:
extrinsic:
gamma: 0.995
strength: 1.0
curiosity:
gamma: 0.99
strength: 0.02
network_settings:
hidden_units: 512
learning_rate: 0.0003
keep_checkpoints: 20
checkpoint_interval: 50000
max_steps: 3000000000
time_horizon: 1000
summary_freq: 10000
threaded: True