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Reinforcement Learning with TensorFlow
book

Reinforcement Learning with TensorFlow

by Sayon Dutta
April 2018
Intermediate to advanced content levelIntermediate to advanced
334 pages
10h 18m
English
Packt Publishing
Content preview from Reinforcement Learning with TensorFlow

Summary

In this chapter, we learned about OpenAI Gym, including the installation of different important functions to load, render, and understand the environment state-action spaces. We learned about the Epsilon-Greedy approach as a solution to the exploration-exploitation dilemma, and tried to implement a basic Q-learning and Q-network algorithm to train a reinforcement-learning agent to navigate an environment from OpenAI Gym.

In the next chapter, we will cover the most fundamental concepts in Reinforcement Learning, which include Markov Decision Processes (MDPs), Bellman Equation, and Markov Chain Monte Carlo.

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Publisher Resources

ISBN: 9781788835725Supplemental Content