To train an RL agent run e.g.
scripts/train_rl.py --env BabyAI-GoToLocal-v0
Folders logs/ and models/ will be created in the current directory. The default name
for the model is chosen based on the level name, the current time and the other settings (e.g.
BabyAI-GoToLocal-v0_ppo_expert_filmcnn_gru_mem_seed1_18-10-12-12-45-02). You can also choose the model
name by setting --model. After 5 hours of training you should be getting a success rate of 97-99%.
A machine readable log can be found in logs/<MODEL>/log.csv, a human readable in logs/<MODEL>/log.log.
To train an agent with IL (imitation learning) first make sure that you have your demonstrations in
demos/<DEMOS> (Instructions to load the demos are present here). Then run e.g.
scripts/train_il.py --env BabyAI-GoToLocal-v0 --demos <DEMOS>
In the example above we run scripts from the root of the repository, but if you have installed BabyAI as
described above, you can also run all scripts with commands like <PATH-TO-BABYAI-REPO>/scripts/train_il.py.
In the same directory where you trained your model run e.g.
scripts/evaluate.py --env BabyAI-GoToLocal-v0 --model <MODEL>
to evaluate the performance of your model named <MODEL> on 1000 episodes. If you want to see
your agent performing, run
scripts/enjoy.py --env BabyAI-GoToLocal-v0 --model <MODEL>