Associative Learning For A Robot Intelligence


Book Description

The explanation of brain functioning in terms of the association of ideas has been popular since the 17th century. Recently, however, the process of association has been dismissed as computationally inadequate by prominent cognitive scientists. In this book, a sharper definition of the term “association” is used to revive the process by showing that associative learning can indeed be computationally powerful. Within an appropriate organization, associative learning can be embodied in a robot to realize a human-like intelligence, which sets its own goals, exhibits unique unformalizable behaviour and has no hidden homunculi.Some believe that artificial intelligence is undergoing a paradigm shift. There are undoubtedly several competing ideas and ideals. Neural networks and dynamic systems are offered as alternatives to the information processing and digital computer models of the brain. One is asked to decide between symbolic and subsymbolic, between algorithmic and nonalgorithmic, and between information processing and interactive systems. Even in the short distance travelled in this book, associative learning is seen to embrace both sides of these dichotomies.




An AGI Brain for a Robot


Book Description

An AGI Brain for a Robot is the first and only book to give a detailed account and practical demonstration of an Artificial General Intelligence (AGI). The brain is to be implemented in fast parallel hardware and embodied in the head of a robot moving in the real world. Associative learning is shown to be a powerful technique for novelty seeking, language learning, and planning. This book is for neuroscientists, robot designers, psychologists, philosophers and anyone curious about the evolution of the human brain and its specialized functions. The overarching message of this book is that an AGI, as the brain of a robot, is within our grasp and would work like our own brains. The featured brain, called PP, is not a computer program. Instead, PP is a collection of networks of associations built from J. A. Fodor's modules and the author's groups. The associations are acquired by intimate interaction between PP in its robot body and the real world. Simulations of PP in one of two robots in a simple world demonstrate PP learning from the second robot, which is under human control. "Both Professor Daniel C. Dennett and Professor Michael A. Arbib independently likened the book 'An AGI Brain for a Robot' to Valentino Braitenberg's 1984 book 'Vehicles: Experiments in Synthetic Psychology'." Daniel C. Dennett, Professor of Philosophy and Director of Center for Cognitive Studies, Tufts University. Author of "From Bacteria to Bach and Back: The Evolution of Minds." "Michael Arbib, a long time expert in brain modeling, observed that sometimes a small book can catch the interest of readers where a large book can overwhelm and turn them away. He noted, in particular, the success of Valentino Braitenberg's 'Vehicles' (for which he wrote the foreword). At a time of explosive interest in AI, he suggests that PP and its antics may be just the right way to ease a larger audience into thinking about the technicalities of creating general artificial intelligence." Michael A Arbib, Professor Emeritus of Computer Science, Biomedical Engineering, Biological Sciences and Psychology, University of Southern California. Author of "How the Brain Got Language". "Robots seem to increasingly invade our lives, to the point that sometimes seems threatening and other-worldly. In this small book, John Andreae shows some of the basic principles of robotics in ways that are entertaining and easily understood, and touch on some of the basic questions of how the mind works." Michael C. Corballis, Professor of Psychology, University of Auckland. Author of "The Recursive Mind". "A little book that punches far beyond its weight." Nicholas Humphrey, Emeritus Professor of Psychology, London School of Economics. Author of "Soul Dust: The Magic of Consciousness". "A bold and rich approach to one of the major challenges for neuroscience, robotics and philosophy. Who will take up Andreae's challenge and implement his model?" Matthew Cobb, Professor of Zoology, University of Manchester. Author of "The Idea of the Brain". "Here is a book that could change the direction of research into artificial general intelligence in a very productive and profitable way. It describes a radical new theory of the brain that goes some way towards answering many difficult questions concerning learning, planning, language, and even consciousness. Almost incredibly, the theory is operational, and expressed in a form that could—and should—inspire future, novel, research in AI that transcends existing paradigms." Ian H. Witten, Professor of Computer Science, Waikato University. Author with Eibe Frank of "Data Mining: Practical Machine Learning Tools and Techniques".




Robot Shaping


Book Description

foreword by Lashon Booker To program an autonomous robot to act reliably in a dynamic environment is a complex task. The dynamics of the environment are unpredictable, and the robots' sensors provide noisy input. A learning autonomous robot, one that can acquire knowledge through interaction with its environment and then adapt its behavior, greatly simplifies the designer's work. A learning robot need not be given all of the details of its environment, and its sensors and actuators need not be finely tuned. Robot Shaping is about designing and building learning autonomous robots. The term "shaping" comes from experimental psychology, where it describes the incremental training of animals. The authors propose a new engineering discipline, "behavior engineering," to provide the methodologies and tools for creating autonomous robots. Their techniques are based on classifier systems, a reinforcement learning architecture originated by John Holland, to which they have added several new ideas, such as "mutespec," classifier system "energy,"and dynamic population size. In the book they present Behavior Analysis and Training (BAT) as an example of a behavior engineering methodology.




Associative Learning for a Robot Intelligence


Book Description

"provides a number of implementation details that will be helpful to anyone following up on PURR-PUSS (PP). The book has an excellent index and a substantial bibliography".Computing Reviews, 1999




Biomimetic Neural Learning for Intelligent Robots


Book Description

This state-of-the-art survey contains selected papers contributed by researchers in intelligent systems, cognitive robotics, and neuroscience including contributions from the MirrorBot project and from the NeuroBotics Workshop 2004. The research work presented demonstrates significant novel developments in biologically inspired neural models for use in intelligent robot environments and biomimetic cognitive behavior.




Artificial Intelligence


Book Description




Neuromorphic Photonic Devices and Applications


Book Description

Neuromorphic Photonic Devices and Applications synthesizes the most critical advances in photonic neuromorphic models, photonic material platforms and accelerators for neuromorphic computing. The book discusses fields and applications that can leverage these new platforms. A brief review of the historical development of the field is followed by a discussion of the emerging 2D photonic materials platforms and recent work in implementing neuromorphic models and 3D neuromorphic systems. The application of artificial intelligence (AI), such as neuromorphic models to inverse design neuromorphic materials and devices and predict performance challenges is discussed throughout. Finally, a comprehensive overview of the applications of neuromorphic photonic technologies and the challenges, opportunities and future prospects is discussed, making the book suitable for researchers and practitioners in academia and R&D in the multidisciplinary field of photonics. - Includes overview of primary scientific concepts for the research topic of neuromorphic photonics such as neurons as computational units, artificial intelligence, machine learning and neuromorphic models - Reviews the latest advances in photonic materials, device platforms and enabling technology drivers of neuromorphic photonics - Discusses potential applications in computing and optical communications




Developmental Robotics


Book Description

A comprehensive overview of an interdisciplinary approach to robotics that takes direct inspiration from the developmental and learning phenomena observed in children's cognitive development. Developmental robotics is a collaborative and interdisciplinary approach to robotics that is directly inspired by the developmental principles and mechanisms observed in children's cognitive development. It builds on the idea that the robot, using a set of intrinsic developmental principles regulating the real-time interaction of its body, brain, and environment, can autonomously acquire an increasingly complex set of sensorimotor and mental capabilities. This volume, drawing on insights from psychology, computer science, linguistics, neuroscience, and robotics, offers the first comprehensive overview of a rapidly growing field. After providing some essential background information on robotics and developmental psychology, the book looks in detail at how developmental robotics models and experiments have attempted to realize a range of behavioral and cognitive capabilities. The examples in these chapters were chosen because of their direct correspondence with specific issues in child psychology research; each chapter begins with a concise and accessible overview of relevant empirical and theoretical findings in developmental psychology. The chapters cover intrinsic motivation and curiosity; motor development, examining both manipulation and locomotion; perceptual development, including face recognition and perception of space; social learning, emphasizing such phenomena as joint attention and cooperation; language, from phonetic babbling to syntactic processing; and abstract knowledge, including models of number learning and reasoning strategies. Boxed text offers technical and methodological details for both psychology and robotics experiments.




Artificial General Intelligence


Book Description

This book constitutes the proceedings of the 11th International Conference on Artificial General Intelligence, AGI 2018, held in Prague, Czech Republic, in August 2018. The 19 regular papers and 10 poster papers presented in this book were carefully reviewed and selected from 52 submissions. The conference encourage interdisciplinary research based on different understandings of intelligence, and exploring different approaches. As the AI field becomes increasingly commercialized and well accepted, maintaining and emphasizing a coherent focus on the AGI goals at the heart of the field remains more critical than ever.




Design and Control of Intelligent Robotic Systems


Book Description

With the increasing applications of intelligent robotic systems in various ?elds, the - sign and control of these systems have increasingly attracted interest from researchers. This edited book entitled “Design and Control of Intelligent Robotic Systems” in the book series of “Studies in Computational Intelligence” is a collection of some advanced research on design and control of intelligent robots. The works presented range in scope from design methodologies to robot development. Various design approaches and al- rithms, such as evolutionary computation, neural networks, fuzzy logic, learning, etc. are included. We also would like to mention that most studies reported in this book have been implemented in physical systems. An overview on the applications of computational intelligence in bio-inspired robotics is given in Chapter 1 by M. Begum and F. Karray, with highlights of the recent progress in bio-inspired robotics research and a focus on the usage of computational intelligence tools to design human-like cognitive abilities in the robotic systems. In Chapter 2, Lisa L. Grant and Ganesh K. Venayagamoorthy present greedy search, particle swarm optimization and fuzzy logic based strategies for navigating a swarm of robots for target search in a hazardous environment, with potential applications in high-risk tasks such as disaster recovery and hazardous material detection.