The Reinforcement Learning Workshop
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The The Reinforcement Learning Workshop
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Author : Alessandro Palmas
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-08-18
The The Reinforcement Learning Workshop written by Alessandro Palmas and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-18 with Computers categories.
Start with the basics of reinforcement learning and explore deep learning concepts such as deep Q-learning, deep recurrent Q-networks, and policy-based methods with this practical guide Key FeaturesUse TensorFlow to write reinforcement learning agents for performing challenging tasksLearn how to solve finite Markov decision problemsTrain models to understand popular video games like BreakoutBook Description Various intelligent applications such as video games, inventory management software, warehouse robots, and translation tools use reinforcement learning (RL) to make decisions and perform actions that maximize the probability of the desired outcome. This book will help you to get to grips with the techniques and the algorithms for implementing RL in your machine learning models. Starting with an introduction to RL, you’ll be guided through different RL environments and frameworks. You’ll learn how to implement your own custom environments and use OpenAI baselines to run RL algorithms. Once you’ve explored classic RL techniques such as Dynamic Programming, Monte Carlo, and TD Learning, you’ll understand when to apply the different deep learning methods in RL and advance to deep Q-learning. The book will even help you understand the different stages of machine-based problem-solving by using DARQN on a popular video game Breakout. Finally, you’ll find out when to use a policy-based method to tackle an RL problem. By the end of The Reinforcement Learning Workshop, you’ll be equipped with the knowledge and skills needed to solve challenging problems using reinforcement learning. What you will learnUse OpenAI Gym as a framework to implement RL environmentsFind out how to define and implement reward functionExplore Markov chain, Markov decision process, and the Bellman equationDistinguish between Dynamic Programming, Monte Carlo, and Temporal Difference LearningUnderstand the multi-armed bandit problem and explore various strategies to solve itBuild a deep Q model network for playing the video game BreakoutWho this book is for If you are a data scientist, machine learning enthusiast, or a Python developer who wants to learn basic to advanced deep reinforcement learning algorithms, this workshop is for you. A basic understanding of the Python language is necessary.
The Reinforcement Learning Workshop
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Author : Alessandro Palmas
language : en
Publisher:
Release Date : 2020
The Reinforcement Learning Workshop written by Alessandro Palmas and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Algorithms categories.
Start with the basics of reinforcement learning and explore deep learning concepts such as deep Q-learning, deep recurrent Q-networks, and policy-based methods with this practical guide Key Features Use TensorFlow to write reinforcement learning agents for performing challenging tasks Learn how to solve finite Markov decision problems Train models to understand popular video games like Breakout Book Description Various intelligent applications such as video games, inventory management software, warehouse robots, and translation tools use reinforcement learning (RL) to make decisions and perform actions that maximize the probability of the desired outcome. This book will help you to get to grips with the techniques and the algorithms for implementing RL in your machine learning models. Starting with an introduction to RL, you'll be guided through different RL environments and frameworks. You'll learn how to implement your own custom environments and use OpenAI baselines to run RL algorithms. Once you've explored classic RL techniques such as Dynamic Programming, Monte Carlo, and TD Learning, you'll understand when to apply the different deep learning methods in RL and advance to deep Q-learning. The book will even help you understand the different stages of machine-based problem-solving by using DARQN on a popular video game Breakout. Finally, you'll find out when to use a policy-based method to tackle an RL problem. By the end of The Reinforcement Learning Workshop, you'll be equipped with the knowledge and skills needed to solve challenging problems using reinforcement learning. What you will learn Use OpenAI Gym as a framework to implement RL environments Find out how to define and implement reward function Explore Markov chain, Markov decision process, and the Bellman equation Distinguish between Dynamic Programming, Monte Carlo, and Temporal Difference Learning Understand the multi-armed bandit problem and explore various strategies to solve it Build a deep Q model network for playing the video game Breakout Who this book is for If you are a data scientist, machine learning enthusiast, or a Python developer who wants to learn basic to advanced deep reinforcement learning algorithms, this workshop is for you. A basic understanding of the Python language is necessary.
Proceedings Of The Sixteenth Annual Conference Of The Cognitive Science Society
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Author : Ashwin Ram
language : en
Publisher: Routledge
Release Date : 2019-05-23
Proceedings Of The Sixteenth Annual Conference Of The Cognitive Science Society written by Ashwin Ram and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-23 with Psychology categories.
This volume features the complete text of all regular papers, posters, and summaries of symposia presented at the 16th annual meeting of the Cognitive Science Society.
Deep Reinforcement Learning
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Author : Aske Plaat
language : en
Publisher: Springer Nature
Release Date : 2022-06-10
Deep Reinforcement Learning written by Aske Plaat and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-10 with Computers categories.
Deep reinforcement learning has attracted considerable attention recently. Impressive results have been achieved in such diverse fields as autonomous driving, game playing, molecular recombination, and robotics. In all these fields, computer programs have taught themselves to understand problems that were previously considered to be very difficult. In the game of Go, the program AlphaGo has even learned to outmatch three of the world’s leading players.Deep reinforcement learning takes its inspiration from the fields of biology and psychology. Biology has inspired the creation of artificial neural networks and deep learning, while psychology studies how animals and humans learn, and how subjects’ desired behavior can be reinforced with positive and negative stimuli. When we see how reinforcement learning teaches a simulated robot to walk, we are reminded of how children learn, through playful exploration. Techniques that are inspired by biology and psychology work amazingly well in computers: animal behavior and the structure of the brain as new blueprints for science and engineering. In fact, computers truly seem to possess aspects of human behavior; as such, this field goes to the heart of the dream of artificial intelligence. These research advances have not gone unnoticed by educators. Many universities have begun offering courses on the subject of deep reinforcement learning. The aim of this book is to provide an overview of the field, at the proper level of detail for a graduate course in artificial intelligence. It covers the complete field, from the basic algorithms of Deep Q-learning, to advanced topics such as multi-agent reinforcement learning and meta learning.
Recent Advances In Reinforcement Learning
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Author : Leslie Pack Kaelbling
language : en
Publisher: Springer
Release Date : 2007-08-28
Recent Advances In Reinforcement Learning written by Leslie Pack Kaelbling and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-28 with Computers categories.
Recent Advances in Reinforcement Learning addresses current research in an exciting area that is gaining a great deal of popularity in the Artificial Intelligence and Neural Network communities. Reinforcement learning has become a primary paradigm of machine learning. It applies to problems in which an agent (such as a robot, a process controller, or an information-retrieval engine) has to learn how to behave given only information about the success of its current actions. This book is a collection of important papers that address topics including the theoretical foundations of dynamic programming approaches, the role of prior knowledge, and methods for improving performance of reinforcement-learning techniques. These papers build on previous work and will form an important resource for students and researchers in the area. Recent Advances in Reinforcement Learning is an edited volume of peer-reviewed original research comprising twelve invited contributions by leading researchers. This research work has also been published as a special issue of Machine Learning (Volume 22, Numbers 1, 2 and 3).
Applied Cryptography And Network Security Workshops
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Author : Jianying Zhou
language : en
Publisher: Springer Nature
Release Date : 2022-09-23
Applied Cryptography And Network Security Workshops written by Jianying Zhou and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-23 with Computers categories.
This book constitutes the proceedings of the satellite workshops held around the 20th International Conference on Applied Cryptography and Network Security, ACNS 2022, held in Rome, Italy, in June 2022. Due to the Corona pandemic the workshop was held as a virtual event. The 31 papers presented in this volume were carefully reviewed and selected from 52 submissions. They stem from the following workshops: – AIBlock: 4th ACNS Workshop on Application Intelligence and Blockchain Security – AIHWS: 3rd ACNS Workshop on Artificial Intelligence in Hardware Security – AIoTS: 4th ACNS Workshop on Artificial Intelligence and Industrial IoT Security – CIMSS: 2nd ACNS Workshop on Critical Infrastructure and Manufacturing System Security – Cloud S&P: 4th ACNS Workshop on Cloud Security and Privacy – SCI: 3rd ACNS Workshop on Secure Cryptographic Implementation – SecMT: 3rd ACNS Workshop on Security in Mobile Technologies – SiMLA: 4th ACNS Workshop on Security in Machine Learning and its Applications
Transfer Learning For Multiagent Reinforcement Learning Systems
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Author : Felipe Leno da Silva
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Transfer Learning For Multiagent Reinforcement Learning Systems written by Felipe Leno da Silva and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
Learning to solve sequential decision-making tasks is difficult. Humans take years exploring the environment essentially in a random way until they are able to reason, solve difficult tasks, and collaborate with other humans towards a common goal. Artificial Intelligent agents are like humans in this aspect. Reinforcement Learning (RL) is a well-known technique to train autonomous agents through interactions with the environment. Unfortunately, the learning process has a high sample complexity to infer an effective actuation policy, especially when multiple agents are simultaneously actuating in the environment. However, previous knowledge can be leveraged to accelerate learning and enable solving harder tasks. In the same way humans build skills and reuse them by relating different tasks, RL agents might reuse knowledge from previously solved tasks and from the exchange of knowledge with other agents in the environment. In fact, virtually all of the most challenging tasks currently solved by RL rely on embedded knowledge reuse techniques, such as Imitation Learning, Learning from Demonstration, and Curriculum Learning. This book surveys the literature on knowledge reuse in multiagent RL. The authors define a unifying taxonomy of state-of-the-art solutions for reusing knowledge, providing a comprehensive discussion of recent progress in the area. In this book, readers will find a comprehensive discussion of the many ways in which knowledge can be reused in multiagent sequential decision-making tasks, as well as in which scenarios each of the approaches is more efficient. The authors also provide their view of the current low-hanging fruit developments of the area, as well as the still-open big questions that could result in breakthrough developments. Finally, the book provides resources to researchers who intend to join this area or leverage those techniques, including a list of conferences, journals, and implementation tools. This book will be useful for a wide audience; and will hopefully promote new dialogues across communities and novel developments in the area.
Proceedings Of The Third International Scientific Conference Intelligent Information Technologies For Industry Iiti 18
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Author : Ajith Abraham
language : en
Publisher: Springer
Release Date : 2018-12-05
Proceedings Of The Third International Scientific Conference Intelligent Information Technologies For Industry Iiti 18 written by Ajith Abraham and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-05 with Technology & Engineering categories.
This book contains papers presented in the main track of IITI 2018, the Third International Scientific Conference on Intelligent Information Technologies for Industry held in Sochi, Russia on September 17–21. The conference was jointly co-organized by Rostov State Transport University (Russia) and VŠB – Technical University of Ostrava (Czech Republic) with the participation of Russian Association for Artificial Intelligence (RAAI). IITI 2018 was devoted to practical models and industrial applications related to intelligent information systems. It was considered as a meeting point for researchers and practitioners to enable the implementation of advanced information technologies into various industries. Nevertheless, some theoretical talks concerning the state-of-the-art in intelligent systems and soft computing were also included into proceedings.
Modern Trends In Controlled Stochastic Processes
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Author : Alexey Piunovskiy
language : en
Publisher: Springer Nature
Release Date : 2021-06-04
Modern Trends In Controlled Stochastic Processes written by Alexey Piunovskiy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-04 with Technology & Engineering categories.
This book presents state-of-the-art solution methods and applications of stochastic optimal control. It is a collection of extended papers discussed at the traditional Liverpool workshop on controlled stochastic processes with participants from both the east and the west. New problems are formulated, and progresses of ongoing research are reported. Topics covered in this book include theoretical results and numerical methods for Markov and semi-Markov decision processes, optimal stopping of Markov processes, stochastic games, problems with partial information, optimal filtering, robust control, Q-learning, and self-organizing algorithms. Real-life case studies and applications, e.g., queueing systems, forest management, control of water resources, marketing science, and healthcare, are presented. Scientific researchers and postgraduate students interested in stochastic optimal control,- as well as practitioners will find this book appealing and a valuable reference.
Artificial Life Vi
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Author : Christoph Adami
language : en
Publisher: MIT Press
Release Date : 1998
Artificial Life Vi written by Christoph Adami and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Computers categories.
Since their inception in 1987, the Artificial Life meetings have grown from small workshops to truly international conferences, reflecting the fields increasing appeal to researchers in all areas of science.