# Reinforcement Learning: Theory and Algorithms (PDF)

**URL:** <https://forum.devtalk.com/t/reinforcement-learning-theory-and-algorithms-pdf/10767>\
**Category:** In The News\
**Tags:** learning, algorithms, in-the-news\
**Created:** [23 June 2021 13:39 UTC](https://forum.devtalk.com/t/reinforcement-learning-theory-and-algorithms-pdf/10767 "2021-06-23T13:39:01Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![CommunityNews](https://forum.devtalk.com/user_avatar/forum.devtalk.com/communitynews/32/1113_2.png) [@CommunityNews](https://forum.devtalk.com/u/CommunityNews)\
**Post date:** [23 June 2021 13:39 UTC](https://forum.devtalk.com/t/reinforcement-learning-theory-and-algorithms-pdf/10767/1 "2021-06-23T13:39:01Z")

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> 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](https://rltheorybook.github.io/rltheorybook_AJKS.pdf)

Details here:

> **[Reinforcement Learning: Theory and Algorithms](https://rltheorybook.github.io/)**
>
> University of Washington. Research interests: Machine Learning, Artificial
> Intelligence, Optimization, Statistics

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