PyTorch 1.x Reinforcement Learning Cookbook电子书

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Preface

Who this book is for

What this book covers

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Download the example code files

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Conventions used

Sections

Getting ready

How to do it…

How it works…

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Reviews

Getting Started with Reinforcement Learning and PyTorch

Setting up the working environment

How to do it...

How it works...

There's more...

See also

Installing OpenAI Gym

How to do it...

How it works...

There's more...

See also

Simulating Atari environments

How to do it...

How it works...

There's more...

See also

Simulating the CartPole environment

How to do it...

How it works...

There's more...

Reviewing the fundamentals of PyTorch

How to do it...

There's more...

See also

Implementing and evaluating a random search policy

How to do it...

How it works...

There's more...

Developing the hill-climbing algorithm

How to do it...

How it works...

There's more...

See also

Developing a policy gradient algorithm

How to do it...

How it works...

There's more...

See also

Markov Decision Processes and Dynamic Programming

Technical requirements

Creating a Markov chain

How to do it...

How it works...

There's more...

See also

Creating an MDP

How to do it...

How it works...

There's more...

See also

Performing policy evaluation

How to do it...

How it works...

There's more...

Simulating the FrozenLake environment

Getting ready

How to do it...

How it works...

There's more...

Solving an MDP with a value iteration algorithm

How to do it...

How it works...

There's more...

Solving an MDP with a policy iteration algorithm

How to do it...

How it works...

There's more...

See also

Solving the coin-flipping gamble problem

How to do it...

How it works...

There's more...

Monte Carlo Methods for Making Numerical Estimations

Calculating Pi using the Monte Carlo method

How to do it...

How it works...

There's more...

See also

Performing Monte Carlo policy evaluation

How to do it...

How it works...

There's more...

Playing Blackjack with Monte Carlo prediction

How to do it...

How it works...

There's more...

See also

Performing on-policy Monte Carlo control

How to do it...

How it works...

There's more...

Developing MC control with epsilon-greedy policy

How to do it...

How it works...

Performing off-policy Monte Carlo control

How to do it...

How it works...

There's more...

See also

Developing MC control with weighted importance sampling

How to do it...

How it works...

There's more...

See also

Temporal Difference and Q-Learning

Setting up the Cliff Walking environment playground

Getting ready

How to do it...

How it works...

Developing the Q-learning algorithm

How to do it...

How it works...

There's more...

Setting up the Windy Gridworld environment playground

How to do it...

How it works...

Developing the SARSA algorithm

How to do it...

How it works...

There's more...

Solving the Taxi problem with Q-learning

Getting ready

How to do it...

How it works...

Solving the Taxi problem with SARSA

How to do it...

How it works...

There's more...

Developing the Double Q-learning algorithm

How to do it...

How it works...

See also

Solving Multi-armed Bandit Problems

Creating a multi-armed bandit environment

How to do it...

How it works...

Solving multi-armed bandit problems with the epsilon-greedy policy

How to do it...

How it works...

There's more...

Solving multi-armed bandit problems with the softmax exploration

How to do it...

How it works...

Solving multi-armed bandit problems with the upper confidence bound algorithm

How to do it...

How it works...

There's more...

See also

Solving internet advertising problems with a multi-armed bandit

How to do it...

How it works...

Solving multi-armed bandit problems with the Thompson sampling algorithm

How to do it...

How it works...

See also

Solving internet advertising problems with contextual bandits

How to do it...

How it works...

Scaling Up Learning with Function Approximation

Setting up the Mountain Car environment playground

Getting ready

How to do it...

How it works...

Estimating Q-functions with gradient descent approximation

How to do it...

How it works...

See also

Developing Q-learning with linear function approximation

How to do it...

How it works...

Developing SARSA with linear function approximation

How to do it...

How it works...

Incorporating batching using experience replay

How to do it...

How it works...

Developing Q-learning with neural network function approximation

How to do it...

How it works...

See also

Solving the CartPole problem with function approximation

How to do it...

How it works...

Deep Q-Networks in Action

Developing deep Q-networks

How to do it...

How it works...

See also

Improving DQNs with experience replay

How to do it...

How it works...

Developing double deep Q-Networks

How to do it...

How it works...

Tuning double DQN hyperparameters for CartPole

How to do it...

How it works...

Developing Dueling deep Q-Networks

How to do it...

How it works...

Applying Deep Q-Networks to Atari games

How to do it...

How it works...

Using convolutional neural networks for Atari games

How to do it...

How it works...

See also

Implementing Policy Gradients and Policy Optimization

Implementing the REINFORCE algorithm

How to do it...

How it works...

See also

Developing the REINFORCE algorithm with baseline

How to do it...

How it works...

Implementing the actor-critic algorithm

How to do it...

How it works...

Solving Cliff Walking with the actor-critic algorithm

How to do it...

How it works...

Setting up the continuous Mountain Car environment

How to do it...

How it works...

Solving the continuous Mountain Car environment with the advantage actor-critic network

How to do it...

How it works...

There's more...

See also

Playing CartPole through the cross-entropy method

How to do it...

How it works...

Capstone Project – Playing Flappy Bird with DQN

Setting up the game environment

Getting ready

How to do it...

How it works...

Building a Deep Q-Network to play Flappy Bird

How to do it...

How it works...

Training and tuning the network

How to do it...

How it works...

Deploying the model and playing the game

How to do it...

How it works...

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