Download or read book MURPHY A Neurally inspired Connectionist Approach to Learning and Performance in Vision based Robot Motion Planning written by Bartlett W. Mel and published by . This book was released on 1989 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Many aspects of intelligent animal behavior require an understanding of the complex spatial relationships between the body and its parts and the coordinate systems of the external world. This thesis deals specifically with the problem of guiding a multi-link arm to a visual target in the presence of obstacles. A simple vision-based kinematic controller and motion planner based on a connectionist network architecture has been developed, called MURPHY. The physical setup consists of a video camera and a Rhino XR-3 robot arm with three joints that move in the image plane of the camera. We assume no a priori model of arm kinematics or of the imaging characteristics of the camera/visual system, and no sophisticated built-in algorithms for obstacle avoidance. Instead, MURPHY builds a model of his arm through a combination of physical and "mental" practice, and then uses simple heuristic search with mental images of his arm to solve visually-guided reaching problems in the presence of obstacles whose traditional algorithmic solutions are extremely complex. MURPHY differs from previous approaches to robot motion-planning primarily in his use of an explicit full-visual-field representation of the workspace. Several other aspects of MURPHY's design are unusual, including the sigma-pi synaptic learning rule, the teacherless training paradigm, and the integration of sequential control within an otherwise connectionist architecture. In concluding sections we outline a series of strong correspondences between the representations and algorithms used by MURPHY, and the psychology, physiology, and neural bases for the programming and control of directed, voluntary arm movements in humans and animals.
Download or read book Connectionist Robot Motion Planning written by Bartlett Mel and published by Elsevier. This book was released on 2013-07-19 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: Connectionist Robot Motion Planning: A Neurally-Inspired Approach to Visually-Guided Reaching is the third series in a cluster of books on robotics and related areas as part of the Perspectives in Artificial Intelligence Series. This series focuses on an experimental paradigm using the MURPHY system to tackle critical issues surrounding robot motion planning. MURPHY is a robot-camera system developed to explore an approach to the kinematics of sensory-motor learning and control for a multi-link arm. Organized into eight chapters, this book describes the guiding of a multi-link arm to visual targets in a cluttered workspace. It primarily focuses on “ecological solutions that are relevant to the typical visually guided reaching behaviors of humans and animals in natural environments. Algorithms that work well in unmodeled workspaces whose effective layouts can change from moment to moment with movements of the eyes, head, limbs, and body are also presented. This book also examines the strengths of neurally inspired connectionist representations and the utility of heuristic search when good performance, even if suboptimal, is adequate for the task. The co-evolution of MURPHY’s design with the brain, presumably in response to similar computational pressures, is described in the concluding chapters, specifically presenting the division of labor between programmed-feedforward and visual-feedback modes of limb control. Design engineers in the fields of biology, neurophysiology, and cognitive psychology will find this book of great value.
Download or read book Cybernetics And Systems 90 Proceedings Of The Tenth European Meeting On Cybernetics And Systems Research written by Robert Trappl and published by World Scientific. This book was released on 1990-03-01 with total page 1130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contents:How Many "Demons" Do We Need? Endophysical Self-Creation of Material Structures and the Exophysical Mystery of Universal Libraries (G Kampis & O E Rössler)Some Implications of Re-Interpretation of the Turing Test for Cognitive Science and Artificial Intelligence (G Werner)Why Economic Forecasts will be Overtaken by the Facts (J D M Kruisinga)Simulation Methods in Peace and Conflict Research (F Breitenecker et al)Software Development Paradigms: A Unifying Concept (G Chroust)Hybrid Hierarchies: A Love-Hate Relationship Between ISA and SUPERC (D Castelfranchi & D D'Aloisi)AI for Social Citizenship: Towards an Anthropocentric Technology (K S Gill)Organizational Cybernetics and Large Scale Social Reforms in the Context of Ongoing Developments (E Bekjarov & A Athanassov)China's Economic Reform and its Obstacles: Challenges to a Large-Scale Social Experiment (J Hu & X Sun)Comparing Conceptual Systems: A Strategy for Changing Values as well as Institutions (S A Umpleby)and others Readership: Researchers in the fields of cybernetics and systems, artificial intelligence, economics and mathematicians.
Download or read book Neuroscience From Neural Networks to Artificial Intelligence written by Pablo Rudomin and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Central Nervous System can be considered as an aggregate of neurons specialized in both the transmission and transformation of information. Information can be used for many purposes, but probably the most important one is to generate a representation of the "external" world that allows the organism to react properly to changes in its external environment. These functions range from such basic ones as detection of changes that may lead to tissue damage and eventual destruction of the organism and the implementation of avoidance reactions, to more elaborate representations of the external world implying recognition of shapes, sounds and textures as the basis of planned action or even reflection. Some of these functions confer a clear survival advantage to the organism (prey or mate recognition, escape reactions, etc. ). Others can be considered as an essential part of cognitive processes that contribute, to varying degrees, to the development of individuality and self-consciousness. How can we hope to understand the complexity inherent in this range of functionalities? One of the distinguishing features of the last two decades has been the availability of computational power that has impacted many areas of science. In neurophysiology, computation is used for experiment control, data analysis and for the construction of models that simulate particular systems. Analysis of the behavior of neuronal networks has transcended the limits of neuroscience and is now a discipline in itself, with potential applications both in the neural sciences and in computing sciences.
Download or read book Machine Learning Proceedings 1991 written by Lawrence A. Birnbaum and published by Morgan Kaufmann. This book was released on 2014-06-28 with total page 682 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning
Download or read book Self Organization Emerging Properties and Learning written by Agnessa Babloyantz and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the proceedings of the workshop held in March 1990 at Austin, Texas on Self-Organization, Emerging Properties and Learning. The workshop was co-sponsored by NATO Scientific Affairs Division, Solvay Institutes of Physics and Chemistry, the University of Texas at Austin and IC2 Institute at Austin. It gathered representatives from a large spectrum of scientific endeavour. The subject matter of self-organization extends over several fields such as hydrodynamics, chemistry, biology, neural networks and social sciences. Several key concepts are common to all these different disciplines. In general the self-organization processes in these fields are described in the framework of the nonlinear dynamics, which also governs the mechanisms underlying the learning processes. Because of this common language, it is expected that any progress in one area could benefit other fields, thus a beneficial cross fertilization may result. In last two decades many workshops and conferences had been organized in various specific fields dealing with self-organization and emerging properties of systems. The aim of the workshop in Austin was to bring together researchers from seemingly unrelated areas and interested in self-organization, emerg{ng properties and learning capabilities of interconnected multi-unit systems. The hope was to initiate interesting exchange and lively discussions. The expectations of the organiziers are materialized in this unusual collection of papers, which brings together in a single volume representative research from many related fields. Thus this volume gives to the reader a wider perspective over the generality and ramifications of the key concepts of self organization.
Download or read book Reinforcement Learning written by Richard S. Sutton and published by Springer Science & Business Media. This book was released on 1992-05-31 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reinforcement learning is the learning of a mapping from situations to actions so as to maximize a scalar reward or reinforcement signal. The learner is not told which action to take, as in most forms of machine learning, but instead must discover which actions yield the highest reward by trying them. In the most interesting and challenging cases, actions may affect not only the immediate reward, but also the next situation, and through that all subsequent rewards. These two characteristics -- trial-and-error search and delayed reward -- are the most important distinguishing features of reinforcement learning. Reinforcement learning is both a new and a very old topic in AI. The term appears to have been coined by Minsk (1961), and independently in control theory by Walz and Fu (1965). The earliest machine learning research now viewed as directly relevant was Samuel's (1959) checker player, which used temporal-difference learning to manage delayed reward much as it is used today. Of course learning and reinforcement have been studied in psychology for almost a century, and that work has had a very strong impact on the AI/engineering work. One could in fact consider all of reinforcement learning to be simply the reverse engineering of certain psychological learning processes (e.g. operant conditioning and secondary reinforcement). Reinforcement Learning is an edited volume of original research, comprising seven invited contributions by leading researchers.
Download or read book The Biology and Technology of Intelligent Autonomous Agents written by Luc Steels and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: The NATO sponsored Advanced Study Institute 'The Biology and Tech nology of Intelligent Autonomous Agents' was an extraordinary event. For two weeks it brought together the leading proponents of the new behavior oriented approach to Artificial Intelligence in Castel Ivano near Trento. The goal of the meeting was to establish a solid scientific and technological foun dation for the field of intelligent autonomous agents with a bias towards the new methodologies and techniques that have recently been developed in Ar tificial Intelligence under the strong influence of biology. Major themes of the conference were: bottom-up AI research, artificial life, neural networks and techniques of emergent functionality. The meeting was such an extraordinary event because it not only featured very high quality lectures on autonomous agents and the various fields feeding it, but also robot laboratories which were set up by the MIT AI laboratory (with a lab led by Rodney Brooks) and the VUB AI laboratory (with labs led by Tim Smithers and Luc Steels). This way the participants could also gain practical experience and discuss in concreto what the difficulties and achievements were of different approaches. In fact, the meeting has been such a success that a follow up meeting is planned for September 1995 in Monte Verita (Switzerland). This meeting is organised by Rolf Pfeifer (University of Zurich).
Download or read book Teleoperation Numerical Simulation and Experimental Validation written by Marc C. Becquet and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on the Lectures given during the Eurocourse on 'Teleoperation: Numerical Simulation and Experimental Validation' held at the Joint Research Centre Ispra, Italy, November 18-22, 1991
Download or read book Explanation Based Neural Network Learning written by Sebastian Thrun and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Competitively Inhibited Neural Networks for Adaptive Parameter Estimation written by Michael Lemmon and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Neural Networks have captured the interest of many researchers in the last five years. As with many young fields, neural network research has been largely empirical in nature, relyingstrongly on simulationstudies ofvarious network models. Empiricism is, of course, essential to any science for it provides a body of observations allowing initial characterization of the field. Eventually, however, any maturing field must begin the process of validating empirically derived conjectures with rigorous mathematical models. It is in this way that science has always pro ceeded. It is in this way that science provides conclusions that can be used across a variety of applications. This monograph by Michael Lemmon provides just such a theoretical exploration of the role ofcompetition in Artificial Neural Networks. There is "good news" and "bad news" associated with theoretical research in neural networks. The bad news isthat such work usually requires the understanding of and bringing together of results from many seemingly disparate disciplines such as neurobiology, cognitive psychology, theory of differential equations, largc scale systems theory, computer science, and electrical engineering. The good news is that for those capable of making this synthesis, the rewards are rich as exemplified in this monograph.
Download or read book COGNITIVA 90 written by Teuvo Kohonen and published by North Holland. This book was released on 1991 with total page 712 pages. Available in PDF, EPUB and Kindle. Book excerpt: The reader of this book will find contributions on a large number of topics, which are addressed either from the Artificial Intelligence or the Neural Networks or the Cognitive Science paradigm. It is through the confrontation of these various contributions that this book offers the reader the most original - and stimulating - perspective. The invited lectures, by outstanding experts, provide global, integrated overviews of their respective domains. The contributed papers offer focused presentations of on-going research work.
Download or read book Dissertation Abstracts International written by and published by . This book was released on 1990 with total page 812 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Learning in Large State Spaces with an Application to Biped Robot Walking written by Thomas U. Vogel and published by . This book was released on 1991 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of the Winter 1990 International Joint Conference on Neural Networks written by Maureen Caudill and published by Taylor & Francis. This book was released on 2022-03-10 with total page 1588 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two volume set provides the complete proceedings of the 1990 International Joint Conference on Neural Networks held in Washington, D.C. Complete with subject, author, and title indices, it provides an invaluable reference to the current state-of-the-art in neural networks. Included in this volume are the latest research results, applications, and products from over 2,000 researchers and application developers from around the world. Ideal as a reference for researchers and practitioners of neuroscience, the two volumes are divided into eight sections: * Neural and Cognitive Sciences * Pattern Recognition and Analysis of Network Dynamics * Learning Theory * Plenary Lecture by Bernard Widrow * Special Lectures on Self-Organizing Neural Architectures * Application Systems and Network Implementations * Robotics, Speech, Signal Processing, and Vision * Expert Systems and Other Real-World Applications
Download or read book Neural Networks written by and published by . This book was released on 1991 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Emergent Computation written by Stephanie Forrest and published by Bradford Book. This book was released on 1991 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Researchers in several fields are exploring computational systems in which interesting global behavior emerges from local interactions among component parts - an approach called emergent computation. In these systems, interactions among simultaneous computations are exploited to improve efficiency, increase flexibility, or provide more realistic models of natural phenomena. These 31 essays define and explore the concept of emergent computation in such areas as artificial networks, adaptive systems, classifier systems, connectionist learning, other learning, and biological networks to determine what properties are required of the supporting architectures that generate them. Many of the essays share the themes of design (how to construct such systems), the importance of preexisting structure to learning and the role of parallelism, and the tension between cooperative and competitive models of interaction. In the introduction, Stephanie Forrest presents several detailed examples of the kinds of problems emergent computation can address. These include showing how emergent computation can lead to efficiency improvements in parallel processing, establishing the connection between emergent computation and nonlinear systems, and comparing two search techniques to show how the emergent-computational approach to a problem differs from other more conventional approaches. Stephanie Forrest is Assistant Professor in the Department of Computer Science at the University of New Mexico. She is also affiliated with the Center for Nonlinear Studies and Computing Division at Los Alamos National Laboratory.
