عنوان
پدید آورنده
موضوع
رده
Q325.5 .R385 2018eb
Q325
.
5
.
R385
2018eb
کتابخانه
محل استقرار
INTERNATIONAL STANDARD BOOK NUMBER
(Number (ISBN
1788836529
(Number (ISBN
178883691X
(Number (ISBN
9781788836524
(Number (ISBN
9781788836913
TITLE AND STATEMENT OF RESPONSIBILITY
Title Proper
Hands-On Reinforcement Learning with Python :
General Material Designation
[Book]
Other Title Information
Master Reinforcement and Deep Reinforcement Learning Using OpenAI Gym and TensorFlow.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Birmingham :
Name of Publisher, Distributor, etc.
Packt Publishing Ltd,
Date of Publication, Distribution, etc.
2018.
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource (309 pages)
GENERAL NOTES
Text of Note
Activation functions.
CONTENTS NOTE
Text of Note
Cover; Title Page; Copyright and Credits; Dedication; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: Introduction to Reinforcement Learning; What is RL?; RL algorithm; How RL differs from other ML paradigms; Elements of RL; Agent; Policy function; Value function; Model; Agent environment interface; Types of RL environment; Deterministic environment; Stochastic environment; Fully observable environment; Partially observable environment; Discrete environment; Continuous environment; Episodic and non-episodic environment; Single and multi-agent environment; RL platforms.
Text of Note
ConstantsPlaceholders; Computation graph; Sessions; TensorBoard; Adding scope; Summary; Questions; Further reading; Chapter 3: The Markov Decision Process and Dynamic Programming; The Markov chain and Markov process; Markov Decision Process; Rewards and returns; Episodic and continuous tasks; Discount factor; The policy function; State value function; State-action value function (Q function); The Bellman equation and optimality; Deriving the Bellman equation for value and Q functions; Solving the Bellman equation; Dynamic programming; Value iteration; Policy iteration.
Text of Note
OpenAI Gym and UniverseDeepMind Lab; RL-Glue; Project Malmo; ViZDoom; Applications of RL; Education; Medicine and healthcare; Manufacturing; Inventory management; Finance; Natural Language Processing and Computer Vision; Summary; Questions; Further reading; Chapter 2: Getting Started with OpenAI and TensorFlow; Setting up your machine; Installing Anaconda; Installing Docker; Installing OpenAI Gym and Universe; Common error fixes; OpenAI Gym; Basic simulations; Training a robot to walk; OpenAI Universe; Building a video game bot; TensorFlow; Variables, constants, and placeholders; Variables.
Text of Note
Solving the frozen lake problemValue iteration; Policy iteration; Summary; Questions; Further reading; Chapter 4: Gaming with Monte Carlo Methods; Monte Carlo methods; Estimating the value of pi using Monte Carlo; Monte Carlo prediction; First visit Monte Carlo; Every visit Monte Carlo; Let's play Blackjack with Monte Carlo; Monte Carlo control; Monte Carlo exploration starts; On-policy Monte Carlo control; Off-policy Monte Carlo control; Summary; Questions; Further reading; Chapter 5: Temporal Difference Learning; TD learning; TD prediction; TD control; Q learning.
Text of Note
Solving the taxi problem using Q learningSARSA; Solving the taxi problem using SARSA; The difference between Q learning and SARSA; Summary; Questions; Further reading; Chapter 6: Multi-Armed Bandit Problem; The MAB problem; The epsilon-greedy policy; The softmax exploration algorithm; The upper confidence bound algorithm; The Thompson sampling algorithm; Applications of MAB; Identifying the right advertisement banner using MAB; Contextual bandits; Summary; Questions; Further reading; Chapter 7: Deep Learning Fundamentals; Artificial neurons; ANNs; Input layer; Hidden layer; Output layer.
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SUMMARY OR ABSTRACT
Text of Note
Reinforcement learning is a self-evolving type of machine learning that takes us closer to achieving true artificial intelligence. This easy-to-follow guide explains everything from scratch using rich examples written in Python.
ACQUISITION INFORMATION NOTE
Source for Acquisition/Subscription Address
01201872
Stock Number
B09792
OTHER EDITION IN ANOTHER MEDIUM
Title
Hands-On Reinforcement Learning with Python : Master Reinforcement and Deep Reinforcement Learning Using OpenAI Gym and TensorFlow.
International Standard Book Number
9781788836524
TOPICAL NAME USED AS SUBJECT
Machine learning.
Artificial intelligence.
Computers-- Intelligence (AI) & Semantics.
Computers-- Neural Networks.
Computers-- Social Aspects-- Human-Computer Interaction.
Human-computer interaction.
Machine learning.
Neural networks & fuzzy systems.
DEWEY DECIMAL CLASSIFICATION
Number
006
.
31
Edition
23
LIBRARY OF CONGRESS CLASSIFICATION
Class number
Q325
.
5
Book number
.
R385
2018eb
PERSONAL NAME - PRIMARY RESPONSIBILITY
Ravichandiran, Sudharsan.
ORIGINATING SOURCE
Date of Transaction
20200823060459.0
Cataloguing Rules (Descriptive Conventions))
pn
ELECTRONIC LOCATION AND ACCESS
Electronic name
مطالعه متن کتاب [Book]
Y
