Proceedings Of The 1993 Connectionist Models Summer School
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Proceedings Of The 1993 Connectionist Models Summer School
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Author : Michael C. Mozer
language : en
Publisher: Psychology Press
Release Date : 2014-03-05
Proceedings Of The 1993 Connectionist Models Summer School written by Michael C. Mozer and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-05 with Psychology categories.
The result of the 1993 Connectionist Models Summer School, the papers in this volume exemplify the tremendous breadth and depth of research underway in the field of neural networks. Although the slant of the summer school has always leaned toward cognitive science and artificial intelligence, the diverse scientific backgrounds and research interests of accepted students and invited faculty reflect the broad spectrum of areas contributing to neural networks, including artificial intelligence, cognitive science, computer science, engineering, mathematics, neuroscience, and physics. Providing an accurate picture of the state of the art in this fast-moving field, the proceedings of this intense two-week program of lectures, workshops, and informal discussions contains timely and high-quality work by the best and the brightest in the neural networks field.
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 : Hao Dong
language : en
Publisher: Springer Nature
Release Date : 2020-06-29
Deep Reinforcement Learning written by Hao Dong and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-29 with Computers categories.
Deep reinforcement learning (DRL) is the combination of reinforcement learning (RL) and deep learning. It has been able to solve a wide range of complex decision-making tasks that were previously out of reach for a machine, and famously contributed to the success of AlphaGo. Furthermore, it opens up numerous new applications in domains such as healthcare, robotics, smart grids and finance. Divided into three main parts, this book provides a comprehensive and self-contained introduction to DRL. The first part introduces the foundations of deep learning, reinforcement learning (RL) and widely used deep RL methods and discusses their implementation. The second part covers selected DRL research topics, which are useful for those wanting to specialize in DRL research. To help readers gain a deep understanding of DRL and quickly apply the techniques in practice, the third part presents mass applications, such as the intelligent transportation system and learning to run, with detailed explanations. The book is intended for computer science students, both undergraduate and postgraduate, who would like to learn DRL from scratch, practice its implementation, and explore the research topics. It also appeals to engineers and practitioners who do not have strong machine learning background, but want to quickly understand how DRL works and use the techniques in their applications.
Artificial Intelligence Applications On Wall Street
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Author : Stephen Slade
language : en
Publisher: Routledge
Release Date : 2017-11-30
Artificial Intelligence Applications On Wall Street written by Stephen Slade and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-30 with Business & Economics categories.
Originally published in 1996 as a special issue journal, Artificial Intelligence Applications on Wall Street, presents a series of articles derived from papers at the Third International Conference on Artificial Intelligence Applications on Wall Street. The volume addresses how Artificial Intelligence can be used to address the variety of issues in that arise in the world of investments, such as synthetic instruments, forecasting and surveillance. It examines the potential problems surrounding economic assumption of rationality in a global market, and how artificial intelligence can push the bounds of rationality.
Advances In Neural Information Processing Systems 7
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Author : Gerald Tesauro
language : en
Publisher: MIT Press
Release Date : 1995
Advances In Neural Information Processing Systems 7 written by Gerald Tesauro and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Computers categories.
November 28-December 1, 1994, Denver, Colorado NIPS is the longest running annual meeting devoted to Neural Information Processing Systems. Drawing on such disparate domains as neuroscience, cognitive science, computer science, statistics, mathematics, engineering, and theoretical physics, the papers collected in the proceedings of NIPS7 reflect the enduring scientific and practical merit of a broad-based, inclusive approach to neural information processing. The primary focus remains the study of a wide variety of learning algorithms and architectures, for both supervised and unsupervised learning. The 139 contributions are divided into eight parts: Cognitive Science, Neuroscience, Learning Theory, Algorithms and Architectures, Implementations, Speech and Signal Processing, Visual Processing, and Applications. Topics of special interest include the analysis of recurrent nets, connections to HMMs and the EM procedure, and reinforcement- learning algorithms and the relation to dynamic programming. On the theoretical front, progress is reported in the theory of generalization, regularization, combining multiple models, and active learning. Neuroscientific studies range from the large-scale systems such as visual cortex to single-cell electrotonic structure, and work in cognitive scientific is closely tied to underlying neural constraints. There are also many novel applications such as tokamak plasma control, Glove-Talk, and hand tracking, and a variety of hardware implementations, with particular focus on analog VLSI.
Reinforcement Learning
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Author : Marco Wiering
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-03-05
Reinforcement Learning written by Marco Wiering and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-05 with Computers categories.
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.
Explanation Based Neural Network Learning
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Author : Sebastian Thrun
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Explanation Based Neural Network Learning written by Sebastian Thrun and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
Lifelong learning addresses situations in which a learner faces a series of different learning tasks providing the opportunity for synergy among them. Explanation-based neural network learning (EBNN) is a machine learning algorithm that transfers knowledge across multiple learning tasks. When faced with a new learning task, EBNN exploits domain knowledge accumulated in previous learning tasks to guide generalization in the new one. As a result, EBNN generalizes more accurately from less data than comparable methods. Explanation-Based Neural Network Learning: A Lifelong Learning Approach describes the basic EBNN paradigm and investigates it in the context of supervised learning, reinforcement learning, robotics, and chess. `The paradigm of lifelong learning - using earlier learned knowledge to improve subsequent learning - is a promising direction for a new generation of machine learning algorithms. Given the need for more accurate learning methods, it is difficult to imagine a future for machine learning that does not include this paradigm.' From the Foreword by Tom M. Mitchell.
Developmental Spans In Event Comprehension And Representation
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Author : Paul van den Broek
language : en
Publisher: Routledge
Release Date : 2013-12-16
Developmental Spans In Event Comprehension And Representation written by Paul van den Broek and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-16 with Language Arts & Disciplines categories.
This book is about building metaphorical bridges--all sorts of bridges. At the most basic level, it concerns the bridges that individuals build to understand the events that they experience--the bridges that connect the events in the mind's eye. At another level, it is about bridges that interconnect findings and theoretical frameworks concerning event comprehension and representation in different age groups, ranging from infancy to adulthood. Finally, it is about building bridges between researchers who share interests, yet may not ordinarily even be aware of each other's work. The success of the book will be measured in terms of the extent to which the contributors have been able to create a picture of the course of development across a wide span in chronological age, and across different types of events, from the fictional to the actual. The individuals whose work is represented in this book conduct their work in a shared environment--they all have an intellectual and scholarly interest in event comprehension and representation. These interests are manifest in the overlapping themes of their work. These include a focus on how people come to temporally integrate individual "snapshots" to form a coherent event that unfolds over time, to understand cause and effect, and to appreciate the role of the goal of events. Another overlapping theme involves the possibility of individual differences. These themes are apparent in work on the early development of representations of specific episodes and autobiographical memories, and comprehension of complex events such as stories involving multiple characters and emotions. The editors of this volume had two missions: * to create a development span by bringing together researchers working from infancy to adulthood, and * to create a bridge between individuals working from within the text comprehension perspective, within the naturalistic perspective, and with laboratory analogues to the naturalistic perspective. Their measure of success will be the extent to which they have been able to create a picture of the course of development across a wide span in chronological age, and across different types of events--from fictional to actual.
Encyclopedia Of Library And Information Science Second Edition
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Author : Miriam Drake
language : en
Publisher: CRC Press
Release Date : 2003-05-20
Encyclopedia Of Library And Information Science Second Edition written by Miriam Drake and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-05-20 with Language Arts & Disciplines categories.
A revitalized version of the popular classic, the Encyclopedia of Library and Information Science, Second Edition targets new and dynamic movements in the distribution, acquisition, and development of print and online media-compiling articles from more than 450 information specialists on topics including program planning in the digital era, recruitment, information management, advances in digital technology and encoding, intellectual property, and hardware, software, database selection and design, competitive intelligence, electronic records preservation, decision support systems, ethical issues in information, online library instruction, telecommuting, and digital library projects.
Continual And Reinforcement Learning For Edge Ai
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Author : Hang Wang
language : en
Publisher: Springer Nature
Release Date : 2025-05-20
Continual And Reinforcement Learning For Edge Ai written by Hang Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-20 with Computers categories.
This book provides a comprehensive introduction to continual and reinforcement learning for edge AI, which investigates how to build an AI agent that can continuously solve new learning tasks and enhance the AI at resource-limited edge devices. The authors introduce readers to practical frameworks and in-depth algorithmic foundations. The book surveys the recent advances in the area, coming from both academic researchers and industry professionals. The authors also present their own research findings on continual and reinforcement learning for edge AI. The book also covers the practical applications of the topic and identifies exciting future research opportunities.