Web: https://www.reddit.com/r/reinforcementlearning/comments/xjegx7/inverse_reinforcement_learning_early_paper_by_ng/

Sept. 20, 2022, 5:10 p.m. | /u/Gclass19

Reinforcement Learning reddit.com

I've been reading one of the first published papers on IRL by Ng & Abbeel \[[link](https://ai.stanford.edu/~ang/papers/icml00-irl.pdf)\], and I'm trying to figure out the shortcoming of the last algorithm proposed in the paper. That algorithm is model-free, does not require given optimal policy (sample trajectories are given instead) and uses linear function approximation for reward functions. So the shortcomings are following:

* imposing structure on reward function
* frequent simulation of trajectories (computational burden)
* reward func is found by optimising …

paper reinforcement reinforcement learning reinforcementlearning

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