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Reinforcement Learning with Torch in Rust: Solving Kuhn Poker

Further experimentations on the tch-rs crate lead me to explore its use in a Reinforcement Learning setting. In this article, I implement a set of neural networks to find an optimal strategy to a simplified two-player game of Poker using Policy Gradient methods applied to multiple interacting agents. The game in question is a toy version of Limit Hold'em Poker called Kuhn Poker. It can be solved analytically which sets a reference to judge the overall performance of the approach.

Read this article Rust Machine Learning Torch

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