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Inverse Reinforcement Learning

See original GitHub issue

Hi,

Firstly, thanks for putting together such an awesome project!

I’ve been playing around with the singleagent.py problems recently and was wondering if there is any way to incorporate demonstration learning / inverse reinforcement learning into these tasks. Instead of hard-coding the reward functions in _computeReward, I wanted to try learning a reward function from expert demonstrations. (See: Let’s do IRL). I’d appreciate if you could give me some pointers on how to modify the _computeReward and the learning process to include an IRL_reward.

Cheers

Issue Analytics

State:
Created 2 years ago
Comments:10 (5 by maintainers)

Top GitHub Comments

1reaction

farbod1277commented, Sep 12, 2021

I fixed it by adding a scaling factor for the thrust and the torques after realising that their scales and clamps are completely different to what DynAviary expects.

0reactions

JacopoPancommented, Sep 12, 2021

I see, I think it can make sense. If you run a few tests and eventually want to create a PR for your modified DSLPIDControlDyn (I’d recommend to subclass from DSLPIDControl for as much as possible), contributions are always welcome!

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