Learning in Games with Side Information PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Learning in Games with Side Information PDF full book. Access full book title Learning in Games with Side Information by Mathieu Sylvestre. Download full books in PDF and EPUB format.
Author: Mathieu Sylvestre
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
This work regards Nash equilibrium-seeking in multi-player finite games. We present a discrete-time algorithm that can be adapted to leverage two forms of side information - a local/global split in the utility structure, where we assume that each player can track the actions of its neighbors and knows the form of its local utility, and unplayed action payoff measurements, where we suppose that players may be capable of observing their hypothetical payoffs for some actions they didn't play - when it is available. We use stochastic approximation to prove that, under mild assumptions, the induced mixed strategies of all players convergence to a perturbed Nash equilibria in games where utilities satisfy certain negative monotonicity properties. We also analyze modifications of the proposed algorithm and prove associated results. All presented results are supported with simulations of certain representative games which illustrate that faster convergence can be obtained when side information is exploited.
Author: Mathieu Sylvestre
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
This work regards Nash equilibrium-seeking in multi-player finite games. We present a discrete-time algorithm that can be adapted to leverage two forms of side information - a local/global split in the utility structure, where we assume that each player can track the actions of its neighbors and knows the form of its local utility, and unplayed action payoff measurements, where we suppose that players may be capable of observing their hypothetical payoffs for some actions they didn't play - when it is available. We use stochastic approximation to prove that, under mild assumptions, the induced mixed strategies of all players convergence to a perturbed Nash equilibria in games where utilities satisfy certain negative monotonicity properties. We also analyze modifications of the proposed algorithm and prove associated results. All presented results are supported with simulations of certain representative games which illustrate that faster convergence can be obtained when side information is exploited.
Author: Fran Blumberg
Publisher: Oxford University Press, USA
ISBN: 019989664X
Category : Education
Languages : en
Pages : 386
Get Book Here
Book Description
There is a growing recognition in the learning sciences that video games can no longer be seen as impediments to education, but rather, they can be developed to enhance learning. Educational and developmental psychologists, education researchers, media psychologists, and cognitive psychologists are now joining game designers and developers in seeking out new ways to use video game play in the classroom. In Learning by Playing, a diverse group of contributors provide perspectives on the most current thinking concerning the ramifications of leisure video game play for academic classroom learning. The first section of the text provides foundational understanding of the cognitive skills and content knowledge that children and adolescents acquire and refine during video game play. The second section explores game features that captivate and promote skills development among game players. The subsequent sections discuss children and adolescents' learning in the context of different types of games and the factors that contribute to transfer of learning from video game play to the classroom. These chapters then form the basis for the concluding section of the text: a specification of the most appropriate research agenda to investigate the academic potential of video game play, particularly using those games that child and adolescent players find most compelling. Contributors include researchers in education, learning sciences, and cognitive and developmental psychology, as well as instructional design researchers.
Author: Marco Wiering
Publisher: Springer Science & Business Media
ISBN: 3642276458
Category : Technology & Engineering
Languages : en
Pages : 653
Get Book Here
Book Description
Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement learning has progressed tremendously in the past decade. The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning. This includes surveys on partially observable environments, hierarchical task decompositions, relational knowledge representation and predictive state representations. Furthermore, topics such as transfer, evolutionary methods and continuous spaces in reinforcement learning are surveyed. In addition, several chapters review reinforcement learning methods in robotics, in games, and in computational neuroscience. In total seventeen different subfields are presented by mostly young experts in those areas, and together they truly represent a state-of-the-art of current reinforcement learning research. Marco Wiering works at the artificial intelligence department of the University of Groningen in the Netherlands. He has published extensively on various reinforcement learning topics. Martijn van Otterlo works in the cognitive artificial intelligence group at the Radboud University Nijmegen in The Netherlands. He has mainly focused on expressive knowledge representation in reinforcement learning settings.
Author: Johannes Fürnkranz
Publisher: Nova Publishers
ISBN: 9781590330210
Category : Computers
Languages : en
Pages : 318
Get Book Here
Book Description
The mind-set that has dominated the history of computer game playing relies on straightforward exploitation of the available computing power. The fact that a machine can explore millions of variations sooner than the sluggish human can wink an eye has inspired hopes that the mystery of intelligence can be cracked, or at least side-stepped, by sheer force. Decades of the steadily growing strength of computer programs have attested to the soundness of this approach. It is clear that deeper understanding can cut the amount of necessary calculations by orders of magnitude. The papers collected in this volume describe how to instill learning skills in game playing machines. The reader is asked to keep in mind that this is not just about games -- the possibility that the discussed techniques will be used in control systems and in decision support always looms in the background.
Author: James Paul Gee
Publisher: Macmillan
ISBN: 1466886420
Category : Education
Languages : en
Pages : 233
Get Book Here
Book Description
Cognitive Development in a Digital Age James Paul Gee begins his classic book with "I want to talk about video games–yes, even violent video games–and say some positive things about them." With this simple but explosive statement, one of America's most well-respected educators looks seriously at the good that can come from playing video games. This revised edition expands beyond mere gaming, introducing readers to fresh perspectives based on games like World of Warcraft and Half-Life 2. It delves deeper into cognitive development, discussing how video games can shape our understanding of the world. An undisputed must-read for those interested in the intersection of education, technology, and pop culture, What Video Games Have to Teach Us About Learning and Literacy challenges traditional norms, examines the educational potential of video games, and opens up a discussion on the far-reaching impacts of this ubiquitous aspect of modern life.
Author: Nicolo Cesa-Bianchi
Publisher: Cambridge University Press
ISBN: 113945482X
Category : Computers
Languages : en
Pages : 4
Get Book Here
Book Description
This important text and reference for researchers and students in machine learning, game theory, statistics and information theory offers a comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical approaches to forecasting, prediction of individual sequences does not impose any probabilistic assumption on the data-generating mechanism. Yet, prediction algorithms can be constructed that work well for all possible sequences, in the sense that their performance is always nearly as good as the best forecasting strategy in a given reference class. The central theme is the model of prediction using expert advice, a general framework within which many related problems can be cast and discussed. Repeated game playing, adaptive data compression, sequential investment in the stock market, sequential pattern analysis, and several other problems are viewed as instances of the experts' framework and analyzed from a common nonstochastic standpoint that often reveals new and intriguing connections.
Author: David J. C. MacKay
Publisher: Cambridge University Press
ISBN: 9780521642989
Category : Computers
Languages : en
Pages : 694
Get Book Here
Book Description
Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.
Author: Karen Schrier
Publisher: Lulu.com
ISBN: 0359984010
Category : Education
Languages : en
Pages : 584
Get Book Here
Book Description
Have you ever wanted to know which games to use in your classroom, library, or afterschool program, or even at home? Which games can help teach preschoolers, K-12, college students, or adults? What can you use for science, literature, or critical thinking skills? This book explores 100 different games and how educators have used the games to teach - what worked and didn't work and their tips and techniques. The list of 100 goes from A to Z Safari to Zoombinis, and includes popular games like Fortnite, Call of Duty: Modern Warfare, and Minecraft, as well as PC, mobile, VR, AR, card and board games.
Author: Richard E. Mayer
Publisher: MIT Press
ISBN: 0262324512
Category : Education
Languages : en
Pages : 303
Get Book Here
Book Description
A comprehensive and up-to-date investigation of what research shows about the educational value of computer games for learning. Many strong claims are made for the educational value of computer games, but there is a need for systematic examination of the research evidence that might support such claims. This book fills that need by providing, a comprehensive and up-to-date investigation of what research shows about learning with computer games. Computer Games for Learning describes three genres of game research: the value-added approach, which compares the learning outcomes of students who learn with a base version of a game to those of students who learn with the base version plus an additional feature; the cognitive consequences approach, which compares learning outcomes of students who play an off-the-shelf computer game for extended periods to those of students who do not; and the media comparative approach, which compares the learning outcomes of students who learn material by playing a game to those of students who learn the same material using conventional media. After introductory chapters that describe the rationale and goals of learning game research as well as the relevance of cognitive science to learning with games, the book offers examples of research in all three genres conducted by the author and his colleagues at the University of California, Santa Barbara; meta-analyses of published research; and suggestions for future research in the field. The book is essential reading for researchers and students of educational games, instructional designers, learning-game developers, and anyone who wants to know what the research has to say about the educational effectiveness of computer games.
Author: William Spaniel
Publisher:
ISBN: 9781492728153
Category : Game theory
Languages : en
Pages : 273
Get Book Here
Book Description
Game Theory 101: The Complete Textbook is a no-nonsense, games-centered introduction to strategic form (matrix) and extensive form (game tree) games. From the first lesson to the last, this textbook introduces games of increasing complexity and then teaches the game theoretical tools necessary to solve them. Quick, efficient, and to the point, Game Theory 101: The Complete Textbook is perfect for introductory game theory, intermediate microeconomics, and political science.
