cyrildever/reinforcement-learning-in-golang
Code for the algorithms of the "Reinforcement Learning" book
This project offers Go language implementations of classic reinforcement learning algorithms, directly adapted from the renowned "Reinforcement Learning - An Introduction" book. It takes descriptions of decision-making problems, like multi-armed bandits or gridworld scenarios, and outputs the code to simulate agents learning optimal strategies. This is ideal for machine learning researchers and students who are exploring reinforcement learning concepts.
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Use this if you are a developer learning about reinforcement learning and want to see how core algorithms, like k-armed bandit or dynamic programming, can be implemented in Go.
Not ideal if you need a production-ready library for deploying reinforcement learning agents, as this project is intended for educational exploration and practice.
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10
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Language
Go
License
MIT
Category
Last pushed
Oct 13, 2024
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