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Reinforcement Learning: Theory and Algorithms (PDF)

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Reinforcement Learning: Theory and Algorithms (PDF)

Modern Artificial Intelligent (AI) systems often need the ability to make sequential decisions in an unknown, uncertain, possibly hostile environment, by actively interacting with the environment to collect relevant data. Reinforcement Learning (RL) is a general framework that can capture the interactive learning setting and has been used to design intelligent agents that achieve super-human level performances on challenging tasks such as Go, computer games, and robotics manipulation.

https://rltheorybook.github.io/rltheorybook_AJKS.pdf

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