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A Concise Introduction To Reinforcement Learning: February 2018 PDF

12 Pages·2020·English
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by ['NirajDhotre']| 2020| 12 pages| English

About A Concise Introduction To Reinforcement Learning: February 2018

This document provides a concise introduction to reinforcement learning which is a form of machine learning that involves an agent learning through trial-and-error interactions with an environment. It highlights some major successes of reinforcement learning, discusses key concepts like Markov decision processes and Bellman equations, and summarizes different algorithms used to solve reinforcement learning problems including Monte Carlo methods, temporal difference learning, and deep Q-networks. The introduction provides useful context on how reinforcement learning relates to and differs from other types of machine learning such as supervised and unsupervised learning.

Detailed Information

Author:['NirajDhotre']
Publication Year:2020
Pages:12
Language:English
Format:PDF
Price:FREE
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