Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. I long for the author that is willing to rewrite the formulas, perhaps using artificial intelligence to compile optimal absorption. --. Compared to Kindle version, printed version: Reviewed in the United States on February 26, 2019. Previous page of related Sponsored Products. Keep math history as a class called math history. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize … Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. Read honest and unbiased product reviews from our users. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. Naturally, first version was delivered and I'm returning it. For the 2020 holiday season, returnable items shipped between October 1 and December 31 can be returned until January 31, 2021. A Bradford Book; second edition (March 1, 1998). Please try again. For example, all figures in color are blurry and faint as if the book was printed with low toners/inks. The book starts with examples and intuitive introduction and definition of reinforcement learning. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Taking the form of numerous applications in finance, network engineering, robot toys, and games, it is clear that his learning paradigm shows even greater promise for future developments. i Reinforcement Learning: An Introduction Second edition, in progress Richard S. Sutton and Andrew G. Barto c 2014, 2015 A Bradford Book The MIT Press I was also familiar with the first edition (1998). I think that the field is more difficult than it needs to be. I mean, a Kalman filter is really only a control system feedback loop of a Bayes equation. There was a problem loading your book clubs. 5 New fromS$94.79. It's a must have if you're in the field of machine learning. Please try your request again later. Find helpful customer reviews and review ratings for Reinforcement Learning – An Introduction (Adaptive Computation and Machine Learning series) at Amazon.com. Find helpful customer reviews and review ratings for Reinforcement Learning: An Introduction at Amazon.com. The representations take a little bit to digest. Amazon Bestsellers Our most popular products based on sales. I always dont write reviews but hands diwn this is it for me.I.love this so much..They only sign to know if people know what they are talking about is to see how they explain the fundamental concepts. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. This is a very readable and comprehensive account of the background, algorithms, applications, and future directions of this pioneering and far-reaching work. Machine learning refers to the use of learning algorithms that build a model of understanding about the relationships between existing data to make predictions about new data. At some point, there are enough names to overload a lifetime of learning. IF we scrapped all of that crap about the names, and worked with names that had logical connections, then the learning would be greatly enhanced. It's the best book of reinforcement learning. Prime members enjoy FREE Delivery and exclusive access to music, movies, TV shows, original audio series, and Kindle books. Ultimate Step by Step Guide to Machine Learning Using Python: Predictive modelling ... An Introduction to Information Theory (Dover Books on Mathematics). Please try your request again later. Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Reviewed in the United Kingdom on August 18, 2019. We work hard to protect your security and privacy. ", Reviewed in the United States on January 26, 2019, An excellent read for anyone looking to learn about Reinforcement Learning, Reviewed in the United States on January 29, 2018. We teach about some people as if they are extraordinary - as if no one else is working on the same things. Book quality is so low, chapter 3 and 4 are repeated twice and only first 7 page of each chapter is in the book. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. Our payment security system encrypts your information during transmission. It introduces all necessary and relevant algorithms for the beginner. To get the free app, enter your mobile phone number. An excellent read for anyone looking to learn about Reinforcement Learning. The only necessary mathematical background is familiarity with elementary concepts of probability. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning … Reviewed in the United Kingdom on May 6, 2014. The spine feels like it's made of cheap cardboard and is not straight not does it cover all the pages. There was an error retrieving your Wish Lists. And the book's quality is also very good. Buy Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning series) second edition by Sutton, Richard S., Barto, Andrew G., Bach, Francis (ISBN: 9780262039246) from Amazon's Book Store. Reinforcement Learning – An Introduction (Adaptive Computation and Machine Learning series) Richard S. Sutton is Professor of Computing Science and AITF Chair in Reinforcement Learning and Artificial Intelligence at the University of Alberta, and also Distinguished Research Scientist at DeepMind. Pattern Recognition and Machine Learning (Information Science and Statistics). Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics). I don't know how this happened but I am returning asap and will try to find an official copy of this book. Its goal is to make actions based on the state it receives, and to maximize the expected cumulative … Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. This shopping feature will continue to load items when the Enter key is pressed. Bring your club to Amazon Book Clubs, start a new book club and invite your friends to join, or find a club that’s right for you for free. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. If anything, the symbolic crafting in this book (and the changes detailing how the symbolic representations have changed) is priceless. TensorFlow Reinforcement Learning Quick Start Guide: Get up and running with traini... Machine Learning: Master Machine Learning Fundamentals For Beginners. Instead, our system considers things like how recent a review is and if the reviewer bought the item on Amazon. Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning) (Adaptive…. Reviewed in the United States on July 5, 2019. Html version @MIT Press @Amazon @chapters/indigo Part 1 deals with defining Reinforcement Learning problems in terms of Markov decision processes. The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. It details how refactoring can make things more understandable. Disappointing. Updated hourly. This is a great book on reinforcement learning. We don’t share your credit card details with third-party sellers, and we don’t sell your information to others. Machine Learning for Algorithmic Trading: Predictive models to extract signals from... Hands-On Data Science for Marketing: Improve your marketing strategies with machine... To calculate the overall star rating and percentage breakdown by star, we don’t use a simple average. Deep Reinforcement Learning with Python: Master classic RL, deep RL, distributional... Machine Learning For Absolute Beginners: A Plain English Introduction (Machine Lear... GANs in Action: Deep learning with Generative Adversarial Networks. Top subscription boxes – right to your door, Adaptive Computation and Machine Learning series, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition…, © 1996-2020, Amazon.com, Inc. or its affiliates. or robotics. Details. However, I received the book with low-quality material and broken cover, and poor printing. Sold by Globalmart Online Shop and ships from Amazon Fulfillment. The pages are not straight. Please try again. Until then, anyone learning more about math history than math will never be a leader in math. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. Although the goal is easy to describe (the closer the robot is to the object, the better), creating the logic … “The second edition of Reinforcement Learning by Sutton and Barto comes at just the right time. Well written, with many examples and a few graphs, and explained mathematical formulas. The covers are shorter than the pages. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. As it is, when you want to learn the fundamentals of math, you are required to learn math history. In order to navigate out of this carousel please use your heading shortcut key to navigate to the next or previous heading. Top subscription boxes – right to your door, Adaptive Computation and Machine Learning series, Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration…, © 1996-2020, Amazon.com, Inc. or its affiliates. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. This book is full of those references, but that is at least what I was looking for. Sold by Globalmart Online Shop and ships from Amazon Fulfillment. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. Buy from Amazon Errata and Notes Full Pdf Without Margins Code Solutions-- send in your solutions for a chapter, get the official ones back (currently incomplete) … The appetite for reinforcement learning among machine learning researchers has never been stronger, as the field has been moving tremendously in the last twenty years. I have taken many courses online about supervised learning but the study material for RL is severely lacking, let alone high quality ones where you can follow and learn this topic in a systematic way. Reinforcement learning (RL) is used to automate decision-making in a variety of domains, including games, autoscaling, finance, robotics, recommendations, and supply chain.Launched at AWS re:Invent 2018, Amazon SageMaker RL helps you quickly build, train, and deploy policies learned by RL. The book is divided into three parts. This book is the solution, you not only can learn the nitty gritty details of the mathematical justification, all the "whys" but also the "hows", the pseudo code are the parts that I enjoy the most. Ray is an open-source … Find all the books, read about the author, and more. The complexity in RL is transformed to joy of RL, Reviewed in the United Kingdom on October 11, 2020. I understand that mathematicians who are publishing new materials must arrive there, I just don't think that the process of getting there needs to be so difficult. Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning) (Adaptive Computation and Machine Learning series). There is enough detail for the reader to be able to implement a decent reinforcement learning algorithm after reading this book. At $57, the quality is utterly unacceptable. Please choose a different delivery location. Reviewed in the United States on March 28, 2019, Disappointing print with low quality. Please try again. I found the monte-carlo sections of this book particularly grueling, but that I think says more about my limits than the content of this book. The final chapter discusses the future societal impacts of reinforcement learning. This book has all the "whats", all the "whys" and all the "hows"! In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. If you don't know about those people, then this book is either ripe for the reading, or a little bit out of reach. By the time of this post, Sutton also has the complete draft of 2017Nov5 which is also public online, which integrated many of the new progress like deep learning, alphaGo, ..etc. Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. These items are shipped from and sold by different sellers. This necessitates a simpler approach equivalent to the building blocks of atoms. Reviewed in the United States on July 13, 2018. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to … The authors summarize the foundations of reinforcement learning, some of this coming from their own work over the last decade. To calculate the overall star rating and percentage breakdown by star, we don’t use a simple average. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. No complaints apart from a minor scuff on the cover, upon delivery. Paperback ₹ 1,987.00 #19. Essential intuitions about Reinforcement Learning, Reviewed in the United States on November 28, 2018. Foundations of Deep Reinforcement Learning: Theory and Practice in Python (Addison-Wesley Data & Analytics Series), Deep Learning (Adaptive Computation and Machine Learning series), Deep Reinforcement Learning Hands-On: Apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more, 2nd Edition, Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series), Reinforcement Learning and Optimal Control, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics). Your recently viewed items and featured recommendations, Select the department you want to search in. There was a problem loading your book clubs. Bring your club to Amazon Book Clubs, start a new book club and invite your friends to join, or find a club that’s right for you for free. Read honest and unbiased product reviews from our users. Reinforcement Learning, second edition: An Introduction (Adaptive Computation and Machine Learning…. Something went wrong. In machine learning circles, there is a lot of buzz about reinforcement learning because it’s an exciting technology with a ton of potential. You're listening to a sample of the Audible audio edition. Algorithms: The Humans in the age of AI. Reviewed in the United States on November 5, 2004. Given a pre-specified reward signal, the RL agent interacts with the environment. I very appreciate their consideration service. Part I defines the reinforcement learning problem in terms of Markov decision processes. Looks like fake especially when compared with my friend's (the one on the left in pictures), Reviewed in the United States on April 6, 2019. Something went wrong. Reinforcement Learning: An Introduction Richard S. Sutton and Andrew G. Barto First Edition (see here for second edition) MIT Press, Cambridge, MA, 1998 A Bradford Book. After viewing product detail pages, look here to find an easy way to navigate back to pages you are interested in. This isn't a simple theory but many of the ideas and methods are practically useful and if you have an interest in neural networks or learning systems then you need to study this book for the six months it deserves!" Reinforcement Learning, second edition: An Introduction (Adaptive Computation and Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. It follows with 3 chapters on the 3 fundamental approaches to reinforcement learning: Dynamic programming, Monte Carlo and Temporal Difference methods. It also analyzes reviews to verify trustworthiness. This shopping feature will continue to load items when the Enter key is pressed. En el libro faltan los ultimos capitulos, como 10 debido a que se trata de la primera edición y no se reseña en ningun sitio. Time for you to start exploring and to expand your skills in Machine Learning with this powerful book for beginners. I will certainly recommend it to all my students and the many other graduate students and researchers who want to get the appropriate context behind the current excitement for RL.”. Everyday low prices and free delivery on eligible orders. It's hard going but worth the effort, if you can stand the relentless bellman equations. Reviewed in the United States on February 2, 2019. The book is divided into 3 parts. The print quality is extremely low. It also analyzes reviews to verify trustworthiness. Its a very good book and the sellers are very nice. Reviewed in the United Kingdom on August 27, 2019, Every single page is lucid, and joy to read. Emphasis on basic concepts as sets, the probability measure associated with sets, sample space, random variables, information measure, and capacity. Probably the best and easiest to read book on R.Learning, Reviewed in the United Kingdom on June 29, 2011. The introduction nd building of concepts explain these guys know what they are talking about, Reviewed in the United States on August 23, 2019. Robotics often involves training complex sequences of behaviors. Reviewed in the United Kingdom on February 19, 2014. Please try again. We will be mentored and guided by the AWS experienced representatives from AWS to learn and apply the reinforcement learning … Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Prime members enjoy FREE Delivery and exclusive access to music, movies, TV shows, original audio series, and Kindle books. THE introduction to reinforcement learning methods. I would say that a class on Abstract ABC's so to speak would allow us to speak in a more abstract fashion and approach math form its constituent parts when building an algorithm. Reviewed in the United Kingdom on November 24, 2019. S$94.79. Hardcover. Find all the books, read about the author, and more. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, and more, Reviewed in the United States on January 28, 2019. FREE delivery: 5 - 10 Nov. Find helpful customer reviews and review ratings for Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning series) at Amazon.com. The widely acclaimed work of Sutton and Barto on reinforcement learning applies some essentials of animal learning, in clever ways, to artificial learning systems. Amazon SageMaker now enables developers and data scientists to quickly and easily develop reinforcement learning models at scale with Amazon SageMaker RL. I have read one third so far. This is mostly because math is one of the most convoluted areas in education. These items are shipped from and sold by different sellers. Before you begin, make sure you are able to read Python script and you have some familiarity with Reinforcement Learning concepts. This is basically the bible of reinforcement learning. Not that there are many books on Reinforcement Learning, but this is probably the best there is. Reinforcement Learning, second edition: An Introduction (Adaptive Computation and Machine Learning series): Sutton, Richard S., Barto, Andrew G.: 9780262039246: Amazon.com: Books. Introduction to Logic Programming (Synthesis Lectures on Artificial Intelligence an... Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control. It's the first edition (no matter what the page says), Reviewed in the United States on May 17, 2020. has been added to your Cart. This book would barely pass as an EE version of a textbook. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. Reinforcement Learning, second edition: An Introduction (Adaptive Computation and Machine Learning series). I know that this book is a bible of RL. New and updated guide about Ai, Machines and Algorithms that influence our life. I'll probably return this item. But the first person to cross the finish line shall be immortalized like a god. Buy from Amazon Errata and Notes Full Pdf Without Margins Code Solutions-- send in your solutions for a chapter, get the official ones back (currently incomplete) … Discover the main player of Silicon Valley and China. There's a problem loading this menu right now. The book has a nice ansatz in that it is a comprehensive review of current techniques in reinforcement learning. Let math be just that - math. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. I read the entire book cover to cover, doing every (non-programming) exercise, as part of a PhD involving RL. Explore this example-packed beginner's guide and start your reinforcement and deep reinforcement learning journey with state-of-the-art algorithms, Bradford Books; second edition (November 13, 2018). Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning series) by Richard S. Sutton , Andrew G. Barto , … I am by no means claiming talent at taking these abstract ideas and presenting them in an easily consumable fashion. Reinforcement Learning: An Introduction Richard S. Sutton and Andrew G. Barto Second Edition (see here for the first edition) MIT Press, Cambridge, MA, 2018. I've already tried "replace order" to fix the book's bad hardcover quality, but looks like that wasn't the only problem. However, the print quality is extremely low. Reviewed in the United States on October 15, 2018, Very good introduction and answers the question of "how do I actually represent error in an online learning system where I do not know what the right answer is? I knew the photo of book cover is from the first edition but the page said "second edition", so I decided to order one, hoping to get the second edition. They answered all the questions I have and try to solve all my concerns. The term machine learning is often used interchangeably with artificial intelligence, but in fact these terms refer to related, but separate, concepts. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning. The … Reviewed in the United States on February 3, 2018. Given the comments complaining about the poor print quality of the (new) book sold by Amazon, I bought the used one. Shantong Zhang who helped replicated all the experiments also have ALL, I mean ALL the experiments implemented in Python, which you can easily find on github. Unfortunately, it is only done as a means of representing the author's work (which is the intent). Reviewed in the United States on January 30, 2019. Everyday low prices and free delivery on eligible orders. Endorsements Code Solutions Figures Errata/notes CourseMaterials. Since that is how the world works, it makes some of the communications easier if we understand this convolution. Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning (ML) models at any scale.In addition to building ML models using more commonly used supervised and unsupervised learning techniques, you can also build reinforcement learning (RL) models using Amazon … For example, consider a robot designed to follow or track another object. Introduction to reinforcement learning Reinforcement learning develops strategies for sequential decision-making problems. Instead, our system considers things like how recent a review is and if the reviewer bought the item on Amazon. This item cannot be shipped to your selected delivery location. This Bootcamp is held by Amazon Web Service (AWS) and Jakarta Machine Learning (JML). It has been extended with modern developments in deep reinforcement learning while extending the scholarly history of the field to modern days. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. One can easily expect spending hundreds of hours to swimming in the details if you want to, thanks to this book, you can also use it as a reference material! To get the free app, enter your mobile phone number. Well written and fairly easy to understand even if you're not a math genius. An introduction to reinforcement learning with AWS RoboMaker. I like the book. Compared to other machine learning materials I have read or watched or listened, this is very well written and they put effort to help you understand. Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning series) (English Edition) eBook: Sutton, Richard S., Barto, Andrew G.: Amazon… Unfortunately, now I only have a single option to return with a $0.00 value because this book is a replacement of my original order. Reinforcement Learning: An Introduction Richard S. Sutton and Andrew G. Barto Second Edition (see here for the first edition) MIT Press, Cambridge, MA, 2018. Richard S. Sutton is Professor of Computing Science and AITF Chair in Reinforcement Learning and Artificial Intelligence at the University of Alberta, and also Distinguished Research Scientist at DeepMind. 4.4 out of 5 stars 9. Your recently viewed items and featured recommendations, Select the department you want to search in. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required. Unable to add item to List. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Read honest and unbiased product reviews from our users. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. The spine bends over backwards when I pick up the book. It explains things adequately. As a subfield of artificial intelligence, reinforcement learning has shown great success from both a theoretical and practical viewpoint. Buy Reinforcement Learning With Python: An Introduction (Adaptive Computation and Machine Learning series) 1 by Broad, Stuart (ISBN: 9781974364022) from Amazon's Book Store. The fundamentals of traditional Logic Programming and the benefits of using the technology to create runnable specifications for complex systems. My (now proved wrong) expectation was to receive a used version of the high-quality printed edition (MIT press); the price ($46) was very close to the new book ($50) so I assumed it was not the same printing. AWS DeepRacer, AWS DeepRacer Evo, and Sensor Kit are now available for shipping outside the United States for purchase on Amazon.com.AWS DeepRacer is the fastest way to get rolling with reinforcement learning (RL), with a fully autonomous 1/18th scale race car driven by reinforcement learning. Very easy to read, covers all basic material (and some more advanced) it is actually a very enjoyable book to read if you are in the field of A.I. Then, you learn how the relationship of the pieces affects the whole. I like it so much! After viewing product detail pages, look here to find an easy way to navigate back to pages you are interested in. ... reinforcement learning, deep learning, and artificial intelligence with Python Hadelin de Ponteves. Part 2nd deals with solutions to dynamic programming and Part 3 incorporates artificial neural networks which are most important while learning Reinforcement Learning. If you want to fully understand the fundamentals of learning agents, this is the textbook to go to and get started with. This book covers the ground essential to understanding much of the work out their published on RL. Recently, I joined a Bootcamp that will start my journey in learning about reinforcement learning (RL). In order to navigate out of this carousel please use your heading shortcut key to navigate to the next or previous heading. Andrew G. Barto is Professor Emeritus in the College of Computer and Information Sciences at the University of Massachusetts Amherst. Reinforcement Learning, s... Watch a recent AWS Twitch stream to learn more. There's a problem loading this menu right now. Roll up your sleeves and start programming AI models - no math or data science background required! No se especfica que la edicion es la primera y que no tienen todos los capítulos. You're listening to a sample of the Audible audio edition.