عنوان
پدید آورنده
موضوع
رده
Q325.6 .D888 2018eb
Q325
.
6
.
D888
2018eb
کتابخانه
محل استقرار
شابک
شابک
1788830717
شابک
1788835727
شابک
9781788830713
شابک
9781788835725
عنوان و نام پديدآور
عنوان اصلي
Reinforcement Learning with TensorFlow :
نام عام مواد
[Book]
ساير اطلاعات عنواني
a beginner's guide to designing self-learning systems with TensorFlow and OpenAI Gym.
وضعیت نشر و پخش و غیره
محل نشرو پخش و غیره
Birmingham :
نام ناشر، پخش کننده و غيره
Packt Publishing,
تاریخ نشرو بخش و غیره
2018.
مشخصات ظاهری
نام خاص و کميت اثر
1 online resource (327 pages)
يادداشت کلی
متن يادداشت
On-policy and off-policy learning.
یادداشتهای مربوط به مندرجات
متن يادداشت
Cover; Title Page; Copyright and Credits; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: Deep Learning -- Architectures and Frameworks; Deep learning; Activation functions for deep learning; The sigmoid function; The tanh function; The softmax function; The rectified linear unit function; How to choose the right activation function; Logistic regression as a neural network; Notation; Objective; The cost function; The gradient descent algorithm; The computational graph; Steps to solve logistic regression using gradient descent; What is xavier initialization?
متن يادداشت
Asynchronous advantage actor-criticIntroduction to TensorFlow and OpenAI Gym; Basic computations in TensorFlow; An introduction to OpenAI Gym; The pioneers and breakthroughs in reinforcement learning; David Silver; Pieter Abbeel; Google DeepMind; The AlphaGo program; Libratus; Summary; Chapter 2: Training Reinforcement Learning Agents Using OpenAI Gym; The OpenAI Gym; Understanding an OpenAI Gym environment; Programming an agent using an OpenAI Gym environment; Q-Learning; The Epsilon-Greedy approach; Using the Q-Network for real-world applications; Summary; Chapter 3: Markov Decision Process.
متن يادداشت
Markov decision processesThe Markov property; The S state set; Actions; Transition model; Rewards; Policy; The sequence of rewards -- assumptions; The infinite horizons; Utility of sequences; The Bellman equations; Solving the Bellman equation to find policies; An example of value iteration using the Bellman equation; Policy iteration; Partially observable Markov decision processes; State estimation; Value iteration in POMDPs; Training the FrozenLake-v0 environment using MDP; Summary; Chapter 4: Policy Gradients; The policy optimization method; Why policy optimization methods?
متن يادداشت
Why do we use xavier initialization?The neural network model; Recurrent neural networks; Long Short Term Memory Networks; Convolutional neural networks; The LeNet-5 convolutional neural network; The AlexNet model; The VGG-Net model; The Inception model; Limitations of deep learning; The vanishing gradient problem; The exploding gradient problem; Overcoming the limitations of deep learning; Reinforcement learning; Basic terminologies and conventions; Optimality criteria; The value function for optimality; The policy model for optimality; The Q-learning approach to reinforcement learning.
متن يادداشت
Why stochastic policy?Example 1 -- rock, paper, scissors; Example 2 -- state aliased grid-world; Policy objective functions; Policy Gradient Theorem; Temporal difference rule; TD(1) rule; TD(0) rule; TD() rule; Policy gradients; The Monte Carlo policy gradient; Actor-critic algorithms; Using a baseline to reduce variance; Vanilla policy gradient; Agent learning pong using policy gradients; Summary; Chapter 5: Q-Learning and Deep Q-Networks; Why reinforcement learning?; Model based learning and model free learning; Monte Carlo learning; Temporal difference learning.
بدون عنوان
0
بدون عنوان
8
بدون عنوان
8
بدون عنوان
8
بدون عنوان
8
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
Reinforcement learning allows you to develop intelligent, self-learning systems. This book shows you how to put the concepts of Reinforcement Learning to train efficient models. You will use popular reinforcement learning algorithms to implement use-cases in image processing and NLP, by combining the power of TensorFlow and OpenAI Gym.
یادداشتهای مربوط به سفارشات
منبع سفارش / آدرس اشتراک
Packt Publishing
شماره انبار
9781788830713
ویراست دیگر از اثر در قالب دیگر رسانه
عنوان
Reinforcement Learning with TensorFlow : A beginner's guide to designing self-learning systems with TensorFlow and OpenAI Gym.
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
Reinforcement learning.
موضوع مستند نشده
Reinforcement learning.
رده بندی ديویی
شماره
006
.
31
ويراست
23
رده بندی کنگره
شماره رده
Q325
.
6
نشانه اثر
.
D888
2018eb
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )
مستند نام اشخاص تاييد نشده
DUTTA, SAYON.
مبدا اصلی
تاريخ عمليات
20200823060455.0
قواعد فهرست نويسي ( بخش توصيفي )
pn
دسترسی و محل الکترونیکی
نام الکترونيکي
مطالعه متن کتاب اطلاعات رکورد کتابشناسی
نوع ماده
[Book]
اطلاعات دسترسی رکورد
تكميل شده
Y
