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The game is in Rust, and so I have been working at using the pytorch Rust bindings, which have an A2C example, so that's what I've been going with. Example here: https://github.com/LaurentMazare/tch-rs/blob/main/examples/reinforcement-learning/a2c.rs
If you're interested in the theoretical foundations of RL, OpenAI's Spinning Up is an amazing resource that goes a bit easier on the math. For the practical side of things, I can't recommend Costa's CleanRL repo more. It has single file (~200ish lines of Python) implementations of most relevant RL algorithms, so it makes it really easy to grasp.
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