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v0.1
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1.7 KiB
Training with Behavioral Cloning
There are a variety of possible imitation learning algorithms which can be used, the simplest one of them is Behavioral Cloning. It works by collecting demonstrations from a teacher, and then simply uses them to directly learn a policy, in the same way the supervised learning for image classification or other traditional Machine Learning tasks work.
Offline Training
With offline behavioral cloning, we can use demonstrations (.demo
files)
generated using the Demonstration Recorder
as the dataset used to train a behavior.
- Choose an agent you would like to learn to imitate some set of demonstrations.
- Record a set of demonstration using the
Demonstration Recorder
(see here). For illustrative purposes we will refer to this file asAgentRecording.demo
. - Build the scene(make sure the Agent is not using its heuristic).
- Open the
config/offline_bc_config.yaml
file. - Modify the
demo_path
parameter in the file to reference the path to the demonstration file recorded in step 2. In our case this is:./UnitySDK/Assets/Demonstrations/AgentRecording.demo
- Launch
mlagent-learn
, providing./config/offline_bc_config.yaml
as the config parameter, and include the--run-id
and--train
as usual. Provide your environment as the--env
parameter if it has been compiled as standalone, or omit to train in the editor. - (Optional) Observe training performance using TensorBoard.
This will use the demonstration file to train a neural network driven agent to directly imitate the actions provided in the demonstration. The environment will launch and be used for evaluating the agent's performance during training.