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I am reading Zeibart's Inverse RL paper, and it states -

The agent is assumed to be attempting to optimize some function that linearly maps the features of each state, $f_{sj} \in \mathbb{R}^k$, to a state reward value representing the agent’s utility for visiting that state."

Can someone please give me an example of state features? I would highly appreciate it if it is in the context of this GitHub repo, wherein the author coded the feature_matrix as a diagonal matrix of shape $N \times D$, where $N$ represents states and $D$ features.

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  • $\begingroup$ Yeah i was also facing this problem. If you knew this plz talk with me here. $\endgroup$
    – Coder
    Jan 30 at 5:10

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