I am working on a project of jet fighters, and I want my agent to learn how to act based on the previous training.
I have trained my agents how to fly towards the target, but I wonder whether I can use this trained onnx file to give inferenece of the new training which let the agent learn how to avoid barriers. OR I have to use curriculum training methods.(Plus: I added some ray cast sensors to the agents for the new training)
Thank you!
I’m not sure how well loading an onnx file back into pytorch will work, but you can use the mlagents-learn --resume option to continue training starting with the learning parameters you have using the last pytorch checkpoint.
If the environment or rewards have changed this amounts to a manual curriculum, but having a scripted curriculum is a good idea so that you can repeat the process again if necessary. If you’ve added new observations since training the model it is probably best to retrain it over again.
You have made it very clear, I think I understand how to proceed . Thank you!