Download or read book Making the world differentiable written by Jürgen Schmidhuber and published by . This book was released on 1990 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book INNC 90 PARIS written by The International Neural Society(INNS), The IEEE Neural and published by Springer Science & Business Media. This book was released on 2013-12-18 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural Networks have been the theater of a dramatic increase of activities in the last five years. The interest of mixing results from fields as different as neurobiology, physics (spin glass theory), mathematics (linear algebra, statistics ... ), computer science (software engineering, hardware architectures ... ) or psychology has attracted a large number of researchers to the field. The perspective of dramatic improvements in many applications has lead important companies to launch new neural network programs and start-ups have mushroomed to address this new market. Throughout the world large programs are being set-up: in Japan the government has committed more than $18 million per year to its 20 year Human Frontier Science program; the DARPA and the US Navy have alloted more than $10 million per year each and other US government agencies are contributing to important but less ambitious programs. Neural networks are also a major research are in the supercomputing initiative. Europe has from the beginning taken an active part in funding major projects in the new field with BRAIN, BRA, ANNIE and PYGMALION (Esprit). Approximately $20 million has been invested to date since 1988 and new programs of nearly $30 million are being funded for the next 3 years. National projects in certain countries may globally double these amounts. Neural network conferences are attracting larger audiences than ever before. Prior to 1987 attendance never surpassed 300. The June 1989 IJCNN conference in Washington had over 2200 participants.
Download or read book Simulating Humans written by Norman I. Badler and published by Oxford University Press, USA. This book was released on 1993-09-02 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: The area of simulated human figures is an active research area in computer graphics, and Norman Badler's group at the University of Pennsylvania is one of the leaders in the field. This book summarizes the state of the art in simulating human figures, discusses many of the interesting application areas, and makes some assumptions and predictions about where the field is going.
Download or read book Why Machines Will Never Rule the World written by Jobst Landgrebe and published by Taylor & Francis. This book was released on 2022-08-12 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book’s core argument is that an artificial intelligence that could equal or exceed human intelligence—sometimes called artificial general intelligence (AGI)—is for mathematical reasons impossible. It offers two specific reasons for this claim: Human intelligence is a capability of a complex dynamic system—the human brain and central nervous system. Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer. In supporting their claim, the authors, Jobst Landgrebe and Barry Smith, marshal evidence from mathematics, physics, computer science, philosophy, linguistics, and biology, setting up their book around three central questions: What are the essential marks of human intelligence? What is it that researchers try to do when they attempt to achieve "artificial intelligence" (AI)? And why, after more than 50 years, are our most common interactions with AI, for example with our bank’s computers, still so unsatisfactory? Landgrebe and Smith show how a widespread fear about AI’s potential to bring about radical changes in the nature of human beings and in the human social order is founded on an error. There is still, as they demonstrate in a final chapter, a great deal that AI can achieve which will benefit humanity. But these benefits will be achieved without the aid of systems that are more powerful than humans, which are as impossible as AI systems that are intrinsically "evil" or able to "will" a takeover of human society.
Download or read book Artificial Intelligence written by Tim Rocktäschel and published by Seven Dials. This book was released on 2024-09-26 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt: "An excellent, extremely up-to-date overview of the most important technological revolution in human history." - Prof. Jeff Clune, University of British Columbia "If I were to recommend one book on AI, this would be it!" - Dr Edward Hughes, LSE & Google DeepMind Explore humanity's most transformative technology: artificial intelligence... In ten short and informative essays, Professor of AI at University College London, Tim Rocktäschel, reveals everything we need to know about artificial intelligence. From what the futures holds for AI and why it continues to improve with more data, to how superhuman AI is attainable and why we still have to fold our own laundry, discover all of this and much, much more! Artificial Intelligence: 10 Things You Should Know is an illuminating and engaging guide to the most important area of science and technology today.
Download or read book From Animals to Animats 2 written by Jean-Arcady Meyer and published by MIT Press. This book was released on 1993 with total page 1018 pages. Available in PDF, EPUB and Kindle. Book excerpt: More than sixty contributions in From Animals to Animats 2 byresearchers in ethology, ecology, cybernetics, artificial intelligence, robotics, and related fieldsinvestigate behaviors and the underlying mechanisms that allow animals and, potentially, robots toadapt and survive in uncertain environments. Jean-Arcady Meyer is Director of Research, CNRS, Paris.Herbert L. Roitblat is Professor of Psychology at the University of Hawaii at Manoa. Stewart W.Wilson is a scientist at The Rowland Institute for Science, Cambridge,Massachusetts. Topics covered: The Animat Approach to Adaptive Behavior,Perception and Motor Control, Action Selection and Behavioral Sequences, Cognitive Maps and InternalWorld Models, Learning, Evolution, Collective Behavior.
Download or read book Metaheuristics written by Mauricio G.C. Resende and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 707 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combinatorial optimization is the process of finding the best, or optimal, so lution for problems with a discrete set of feasible solutions. Applications arise in numerous settings involving operations management and logistics, such as routing, scheduling, packing, inventory and production management, lo cation, logic, and assignment of resources. The economic impact of combi natorial optimization is profound, affecting sectors as diverse as transporta tion (airlines, trucking, rail, and shipping), forestry, manufacturing, logistics, aerospace, energy (electrical power, petroleum, and natural gas), telecommu nications, biotechnology, financial services, and agriculture. While much progress has been made in finding exact (provably optimal) so lutions to some combinatorial optimization problems, using techniques such as dynamic programming, cutting planes, and branch and cut methods, many hard combinatorial problems are still not solved exactly and require good heuristic methods. Moreover, reaching "optimal solutions" is in many cases meaningless, as in practice we are often dealing with models that are rough simplifications of reality. The aim of heuristic methods for combinatorial op timization is to quickly produce good-quality solutions, without necessarily providing any guarantee of solution quality. Metaheuristics are high level procedures that coordinate simple heuristics, such as local search, to find solu tions that are of better quality than those found by the simple heuristics alone: Modem metaheuristics include simulated annealing, genetic algorithms, tabu search, GRASP, scatter search, ant colony optimization, variable neighborhood search, and their hybrids.
Download or read book Deep Reinforcement Learning written by Aske Plaat and published by Springer Nature. This book was released on 2022-06-10 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Deep Generative Modeling written by Jakub M. Tomczak and published by Springer Nature. This book was released on 2022-02-18 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook tackles the problem of formulating AI systems by combining probabilistic modeling and deep learning. Moreover, it goes beyond typical predictive modeling and brings together supervised learning and unsupervised learning. The resulting paradigm, called deep generative modeling, utilizes the generative perspective on perceiving the surrounding world. It assumes that each phenomenon is driven by an underlying generative process that defines a joint distribution over random variables and their stochastic interactions, i.e., how events occur and in what order. The adjective "deep" comes from the fact that the distribution is parameterized using deep neural networks. There are two distinct traits of deep generative modeling. First, the application of deep neural networks allows rich and flexible parameterization of distributions. Second, the principled manner of modeling stochastic dependencies using probability theory ensures rigorous formulation and prevents potential flaws in reasoning. Moreover, probability theory provides a unified framework where the likelihood function plays a crucial role in quantifying uncertainty and defining objective functions. Deep Generative Modeling is designed to appeal to curious students, engineers, and researchers with a modest mathematical background in undergraduate calculus, linear algebra, probability theory, and the basics in machine learning, deep learning, and programming in Python and PyTorch (or other deep learning libraries). It will appeal to students and researchers from a variety of backgrounds, including computer science, engineering, data science, physics, and bioinformatics, who wish to become familiar with deep generative modeling. To engage the reader, the book introduces fundamental concepts with specific examples and code snippets. The full code accompanying the book is available on github. The ultimate aim of the book is to outline the most important techniques in deep generative modeling and, eventually, enable readers to formulate new models and implement them.
Download or read book Generative Adversarial Learning Architectures and Applications written by Roozbeh Razavi-Far and published by Springer Nature. This book was released on 2022-03-11 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a collection of recent research works addressing theoretical issues on improving the learning process and the generalization of GANs as well as state-of-the-art applications of GANs to various domains of real life. Adversarial learning fascinates the attention of machine learning communities across the world in recent years. Generative adversarial networks (GANs), as the main method of adversarial learning, achieve great success and popularity by exploiting a minimax learning concept, in which two networks compete with each other during the learning process. Their key capability is to generate new data and replicate available data distributions, which are needed in many practical applications, particularly in computer vision and signal processing. The book is intended for academics, practitioners, and research students in artificial intelligence looking to stay up to date with the latest advancements on GANs’ theoretical developments and their applications.
Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Download or read book Anticipatory Behavior in Adaptive Learning Systems written by Giovanni Pezzulo and published by Springer. This book was released on 2009-06-18 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Anticipatory behavior in adaptive learning systems continues attracting attention of researchers in many areas, including cognitive systems, neuroscience, psychology, and machine learning. This book constitutes the thoroughly refereed post-workshop proceedings of the 4th International Workshop on Anticipatory Behavior in Adaptive Learning Systems, ABiALS 2008, held in Munich, Germany, in June 2008, in collaboration with the six-monthly Meeting of euCognition 'The Role of Anticipation in Cognition'. The 18 revised full papers presented were carefully selected during two rounds of reviewing and improvement for inclusion in the book. The introductory chapter of this state-of-the-art survey not only provides an overview of the contributions included in this volume but also revisits the current available terminology on anticipatory behavior and relates it to the available system approaches. The papers are organized in topical sections on anticipation in psychology with focus on the ideomotor view, conceptualizations, anticipation and dynamical systems, computational modeling of psychological processes in the individual and social domains, behavioral and cognitive capabilities based on anticipation, and computational frameworks and algorithms for anticipation, and their evaluation.
Download or read book XxAI Beyond Explainable AI written by Andreas Holzinger and published by Springer Nature. This book was released on 2022 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an open access book. Statistical machine learning (ML) has triggered a renaissance of artificial intelligence (AI). While the most successful ML models, including Deep Neural Networks (DNN), have developed better predictivity, they have become increasingly complex, at the expense of human interpretability (correlation vs. causality). The field of explainable AI (xAI) has emerged with the goal of creating tools and models that are both predictive and interpretable and understandable for humans. Explainable AI is receiving huge interest in the machine learning and AI research communities, across academia, industry, and government, and there is now an excellent opportunity to push towards successful explainable AI applications. This volume will help the research community to accelerate this process, to promote a more systematic use of explainable AI to improve models in diverse applications, and ultimately to better understand how current explainable AI methods need to be improved and what kind of theory of explainable AI is needed. After overviews of current methods and challenges, the editors include chapters that describe new developments in explainable AI. The contributions are from leading researchers in the field, drawn from both academia and industry, and many of the chapters take a clear interdisciplinary approach to problem-solving. The concepts discussed include explainability, causability, and AI interfaces with humans, and the applications include image processing, natural language, law, fairness, and climate science.
Download or read book INNC 90 Paris written by and published by . This book was released on 1990 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Artificial Intelligence written by David L. Poole and published by Cambridge University Press. This book was released on 2023-07-13 with total page 898 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fully revised and updated, this third edition includes three new chapters on neural networks and deep learning including generative AI, causality, and the social, ethical and regulatory impacts of artificial intelligence. All parts have been updated with the methods that have been proven to work. The book's novel agent design space provides a coherent framework for learning, reasoning and decision making. Numerous realistic applications and examples facilitate student understanding. Every concept or algorithm is presented in pseudocode and open source AIPython code, enabling students to experiment with and build on the implementations. Five larger case studies are developed throughout the book and connect the design approaches to the applications. Each chapter now has a social impact section, enabling students to understand the impact of the various techniques as they learn them. An invaluable teaching package for undergraduate and graduate AI courses, this comprehensive textbook is accompanied by lecture slides, solutions, and code.
Download or read book The Challenge of Anticipation written by Giovanni Pezzulo and published by Springer. This book was released on 2008-09-25 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: The general idea that brains anticipate the future, that they engage in prediction, and that one means of doing this is through some sort of inner model that can be run of?ine,hasalonghistory. SomeversionoftheideawascommontoAristotle,aswell as to many medieval scholastics, to Leibniz and Hume, and in more recent times, to Kenneth Craik and Philip Johnson-Laird. One reason that this general idea recurs continually is that this is the kind of picture that introspection paints. When we are engaged in tasks it seems that we form images that are predictions, or anticipations, and that these images are isomorphic to what they represent. But as much as the general idea recurs, opposition to it also recurs. The idea has never been widely accepted, or uncontroversial among psychologists, cognitive scientists and neuroscientists. The main reason has been that science cannot be s- is?ed with metaphors and introspection. In order to gain acceptance, an idea needs to be formulated clearly enough so that it can be used to construct testable hypot- ses whose results will clearly supportor cast doubtupon the hypothesis. Next, those ideasthatare formulablein one oranothersortof symbolismor notationare capable of being modeled, and modeling is a huge part of cognitive neuroscience. If an idea cannot be clearly modeled, then there are limits to how widely it can be tested and accepted by a cognitive neuroscience community.
Download or read book Active Inference written by Christopher L. Buckley and published by Springer Nature. This book was released on 2023-12-17 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the papers of the 4th International Workshop on Active Inference, IWAI 2023, held in Ghent, Belgium on September 2023. The 17 full papers included in this book were carefully reviewed and selected from 34 submissions. They were organized in topical sections as follows: active inference and robotics; decision-making and control; active inference and psychology; from theory to implementation; learning representations for active inference; and theory of learning and inference.
