Information Theoretic Principles for Agent Learning
Author : Jerry D. Gibson
Publisher : Springer Nature
Page : 99 pages
File Size : 19,16 MB
Release :
Category :
ISBN : 3031653882
Foundations of Machine Learning, second edition
Author : Mehryar Mohri
Publisher : MIT Press
Page : 505 pages
File Size : 46,49 MB
Release : 2018-12-25
Category : Computers
ISBN : 0262351366
Book Description
A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning is unique in its focus on the analysis and theory of algorithms. The first four chapters lay the theoretical foundation for what follows; subsequent chapters are mostly self-contained. Topics covered include the Probably Approximately Correct (PAC) learning framework; generalization bounds based on Rademacher complexity and VC-dimension; Support Vector Machines (SVMs); kernel methods; boosting; on-line learning; multi-class classification; ranking; regression; algorithmic stability; dimensionality reduction; learning automata and languages; and reinforcement learning. Each chapter ends with a set of exercises. Appendixes provide additional material including concise probability review. This second edition offers three new chapters, on model selection, maximum entropy models, and conditional entropy models. New material in the appendixes includes a major section on Fenchel duality, expanded coverage of concentration inequalities, and an entirely new entry on information theory. More than half of the exercises are new to this edition.
The Principles of Deep Learning Theory
Author : Daniel A. Roberts
Publisher : Cambridge University Press
Page : 473 pages
File Size : 26,95 MB
Release : 2022-05-26
Category : Computers
ISBN : 1316519333
Book Description
This volume develops an effective theory approach to understanding deep neural networks of practical relevance.
Artificial Cognitive Architecture with Self-Learning and Self-Optimization Capabilities
Author : Gerardo Beruvides
Publisher : Springer
Page : 216 pages
File Size : 38,6 MB
Release : 2018-12-14
Category : Technology & Engineering
ISBN : 3030039498
Book Description
This book introduces three key issues: (i) development of a gradient-free method to enable multi-objective self-optimization; (ii) development of a reinforcement learning strategy to carry out self-learning and finally, (iii) experimental evaluation and validation in two micromachining processes (i.e., micro-milling and micro-drilling). The computational architecture (modular, network and reconfigurable for real-time monitoring and control) takes into account the analysis of different types of sensors, processing strategies and methodologies for extracting behavior patterns from representative process’ signals. The reconfiguration capability and portability of this architecture are supported by two major levels: the cognitive level (core) and the executive level (direct data exchange with the process). At the same time, the architecture includes different operating modes that interact with the process to be monitored and/or controlled. The cognitive level includes three fundamental modes such as modeling, optimization and learning, which are necessary for decision-making (in the form of control signals) and for the real-time experimental characterization of complex processes. In the specific case of the micromachining processes, a series of models based on linear regression, nonlinear regression and artificial intelligence techniques were obtained. On the other hand, the executive level has a constant interaction with the process to be monitored and/or controlled. This level receives the configuration and parameterization from the cognitive level to perform the desired monitoring and control tasks.
Cybernetical Intelligence
Author : Kelvin K. L. Wong
Publisher : John Wiley & Sons
Page : 436 pages
File Size : 43,29 MB
Release : 2023-10-31
Category : Computers
ISBN : 139421748X
Book Description
Highly comprehensive, detailed, and up-to-date overview of artificial intelligence and cybernetics, with practical examples and supplementary learning resources Cybernetical Intelligence: Engineering Cybernetics with Machine Intelligence is a comprehensive guide to the field of cybernetics and neural networks, , as well as the mathematical foundations of these technologies. The book provides a detailed explanation of various types of neural networks, including feedforward networks, recurrent neural networks, and convolutional neural networks, and their applications to different real-world problems. This groundbreaking book presents a pioneering exploration of machine learning within the framework of cybernetics. It marks a significant milestone in the field's history, as it is the first book to describe the development of machine learning from a cybernetics perspective. The introduction of the concept of "Cybernetical Intelligence" and the generation of new terminology within this context propel new lines of thought in the historical development of artificial intelligence. With its profound implications and contributions, this book holds immense importance and is poised to become a definitive resource for scholars and researchers in this field of study. Each chapter is specifically designed to introduce the theory with several examples. This comprehensive book includes exercise questions at the end of each chapter, providing readers with valuable opportunities to apply and strengthen their understanding of cybernetical intelligence. To further support the learning journey, solutions to these questions are readily accessible on our book's companion site. Additionally, the companion site offers programming practice exercises and assignments, enabling readers to delve deeper into the practical aspects of the subject matter. Cybernetical Intelligence includes information on: History and development of cybernetics and its influence on the development of neural networks Developments and innovations in artificial intelligence and machine learning, such as deep reinforcement learning, generative adversarial networks, and transfer learning Mathematical foundations of artificial intelligence and cybernetics, including linear algebra, calculus, and probability theory Ethical implications of artificial intelligence and cybernetics, and responsible and transparent development and deployment of AI systems Presenting a highly detailed and comprehensive overview of the field, with modern developments thoroughly discussed, Cybernetical Intelligence is an essential textbook resource that helps students make connections with the real-life engineering problems by providing both theory and practice, along with a myriad of helpful learning aids.
Handbook of Research on Complex Dynamic Process Management: Techniques for Adaptability in Turbulent Environments
Author : Wang, Minhong
Publisher : IGI Global
Page : 691 pages
File Size : 37,44 MB
Release : 2009-07-31
Category : Education
ISBN : 160566670X
Book Description
Investigates the nature and history of dynamic processes essential to understanding the need for flexibility and adaptability as well as the requirements to improve solutions.
Adaptive Agents and Multi-Agent Systems III. Adaptation and Multi-Agent Learning
Author : Karl Tuyls
Publisher : Springer
Page : 263 pages
File Size : 46,14 MB
Release : 2008-02-09
Category : Computers
ISBN : 3540779493
Book Description
This book contains selected and revised papers of the European Symposium on Adaptive and Learning Agents and Multi-Agent Systems (ALAMAS), editions 2005, 2006 and 2007, held in Paris, Brussels and Maastricht. The goal of the ALAMAS symposia, and this associated book, is to increase awareness and interest in adaptation and learning for single agents and mul- agent systems, and encourage collaboration between machine learning experts, softwareengineeringexperts,mathematicians,biologistsandphysicists,andgive a representative overviewof current state of a?airs in this area. It is an inclusive forum where researchers can present recent work and discuss their newest ideas for a ?rst time with their peers. Thesymposiaseriesfocusesonallaspectsofadaptiveandlearningagentsand multi-agent systems, with a particular emphasis on how to modify established learning techniques and/or create new learning paradigms to address the many challenges presented by complex real-world problems. These symposia were a great success and provided a forum for the pres- tation of new ideas and results bearing on the conception of adaptation and learning for single agents and multi-agent systems. Over these three editions we received 51 submissions, of which 17 were carefully selected, including one invited paper of this year’s invited speaker Simon Parsons. This is a very c- petitive acceptance rate of approximately 31%, which, together with two review cycles, has led to a high-quality LNAI volume. We hope that our readers will be inspired by the papers included in this volume.
Human Centered Computing
Author : Danijela Milošević
Publisher : Springer Nature
Page : 729 pages
File Size : 48,83 MB
Release : 2020-01-20
Category : Computers
ISBN : 3030374297
Book Description
This book constitutes thoroughly reviewed, revised and selected papers from the 5th International Conference on Human Centered Computing, HCC 2019, held in Čačak, Serbia, in August 2019. The 48 full and 23 short papers presented in this volume were carefully reviewed and selected from a total of 133 submissions. The papers focus on deep learning and its applications on a variety of real-life problems, ranging from image/video analysis, to human-computer interaction, and to logistics and supply chain management.
Information Theory and Statistical Learning
Author : Frank Emmert-Streib
Publisher : Springer Science & Business Media
Page : 443 pages
File Size : 31,48 MB
Release : 2009
Category : Computers
ISBN : 0387848150
Book Description
This interdisciplinary text offers theoretical and practical results of information theoretic methods used in statistical learning. It presents a comprehensive overview of the many different methods that have been developed in numerous contexts.
Guided Self-Organization: Inception
Author : Mikhail Prokopenko
Publisher : Springer Science & Business Media
Page : 488 pages
File Size : 13,95 MB
Release : 2013-12-19
Category : Technology & Engineering
ISBN : 3642537340
Book Description
Is it possible to guide the process of self-organisation towards specific patterns and outcomes? Wouldn’t this be self-contradictory? After all, a self-organising process assumes a transition into a more organised form, or towards a more structured functionality, in the absence of centralised control. Then how can we place the guiding elements so that they do not override rich choices potentially discoverable by an uncontrolled process? This book presents different approaches to resolving this paradox. In doing so, the presented studies address a broad range of phenomena, ranging from autopoietic systems to morphological computation, and from small-world networks to information cascades in swarms. A large variety of methods is employed, from spontaneous symmetry breaking to information dynamics to evolutionary algorithms, creating a rich spectrum reflecting this emerging field. Demonstrating several foundational theories and frameworks, as well as innovative practical implementations, Guided Self-Organisation: Inception, will be an invaluable tool for advanced students and researchers in a multiplicity of fields across computer science, physics and biology, including information theory, robotics, dynamical systems, graph theory, artificial life, multi-agent systems, theory of computation and machine learning.
