Self-Organization, Computational Maps, and Motor Control


Book Description

In the study of the computational structure of biological/robotic sensorimotor systems, distributed models have gained center stage in recent years, with a range of issues including self-organization, non-linear dynamics, field computing etc. This multidisciplinary research area is addressed here by a multidisciplinary team of contributors, who provide a balanced set of articulated presentations which include reviews, computational models, simulation studies, psychophysical, and neurophysiological experiments.The book is divided into three parts, each characterized by a slightly different focus: in part I, the major theme concerns computational maps which typically model cortical areas, according to a view of the sensorimotor cortex as "geometric engine" and the site of "internal models" of external spaces. Part II also addresses problems of self-organization and field computing, but in a simpler computational architecture which, although lacking a specialized cortical machinery, can still behave in a very adaptive and surprising way by exploiting the interaction with the real world. Finally part III is focused on the motor control issues related to the physical properties of muscular actuators and the dynamic interactions with the world.The reader will find different approaches on controversial issues, such as the role and nature of force fields, the need for internal representations, the nature of invariant commands, the vexing question about coordinate transformations, the distinction between hierachiacal and bi-directional modelling, and the influence of muscle stiffness.




Self-Organization in the Evolution of Speech


Book Description

Speech is the principal supporting medium of language. In this book Pierre-Yves Oudeyer considers how spoken language first emerged. He presents an original and integrated view of the interactions between self-organization and natural selection, reformulates questions about the origins of speech, and puts forward what at first sight appears to be a startling proposal - that speech can be spontaneously generated by the coupling of evolutionarily simple neural structures connecting perception and production. He explores this hypothesis by constructing a computational system to model the effects of linking auditory and vocal motor neural nets. He shows that a population of agents which used holistic and unarticulated vocalizations at the outset are inexorably led to a state in which their vocalizations have become discrete, combinatorial, and categorized in the same way by all group members. Furthermore, the simple syntactic rules that have emerged to regulate the combinations of sounds exhibit the fundamental properties of modern human speech systems. This original and fascinating account will interest all those interested in the evolution of speech.




Neural Nets WIRN VIETRI-98


Book Description

From its early beginnings in the fifties and sixties, the field of neural networks has been steadily developing to become one of the most interdisciplinary areas of research within computer science. This volume contains selected papers from WIRN Vietri-98, the 10th Italian Workshop on Neural Nets, 21-23 May 1998, Vietri sul Mare, Salerno, Italy. This annual event, sponsored amongst others by the IEEE Neural Network Council and the INNS/SIG Italy, brings together the best of research from all over the world. The papers cover a range of key topics within neural networks, including pattern recognition, signal processing, hybrid systems, mathematical models, hardware and software design, and fuzzy techniques. It also includes two review talks on a Morpho-Functional Model to Describe Variability Found at Hippocampal Synapses and Neural Networks and Speech Processing. By providing the reader with a comprehensive overview of recent research in this area, the volume makes a valuable contribution to the Perspectives in Neural Computing Series.




Kohonen Maps


Book Description

The Self-Organizing Map, or Kohonen Map, is one of the most widely used neural network algorithms, with thousands of applications covered in the literature. It was one of the strong underlying factors in the popularity of neural networks starting in the early 80's. Currently this method has been included in a large number of commercial and public domain software packages. In this book, top experts on the SOM method take a look at the state of the art and the future of this computing paradigm.The 30 chapters of this book cover the current status of SOM theory, such as connections of SOM to clustering, classification, probabilistic models, and energy functions. Many applications of the SOM are given, with data mining and exploratory data analysis the central topic, applied to large databases of financial data, medical data, free-form text documents, digital images, speech, and process measurements. Biological models related to the SOM are also discussed.




Human and Machine Perception


Book Description

The following are th€:" proceedings of the Second International Workshop on Human and Machine Perception held in Trabia, Italy, on July 21~25, 1996, under the auspices of two Institutions: the Cybernetic and Biophysics Group (GNCB) of the Italian National Research Council (CNR) and the 'Centro Interdipartimentale di Tecnologie della Conoscenza' ofPalenno University. A broad spectrum of topics are covered in this series, ranging from computer perception to psychology and physiology of perception (visual, auditory, tactile, etc.). The theme of this workshop was: "Human and Machine Perception: Information Fusion". The goal of information and sensory data fusion is to integrate internal knowledge with complementary and/or redundant information from many sensors to achieve (and maintain) a better knowledge of the environment. The mechanism behind the integration of information is one of the most difficult challenges in understanding human and robot perception. The workshop consisted of a pilot phase of eight leCtures introducing perception sensorialities in nature and artificial systems, and of five subsequent modules each consisting of two lectures (dealing with solutions in nature and machines respectively) and a panel discussion.




Quantum Machine Learning


Book Description

Quantum-enhanced machine learning refers to quantum algorithms that solve tasks in machine learning, thereby improving a classical machine learning method. Such algorithms typically require one to encode the given classical dataset into a quantum computer, so as to make it accessible for quantum information processing. After this, quantum information processing routines can be applied and the result of the quantum computation is read out by measuring the quantum system. While many proposals of quantum machine learning algorithms are still purely theoretical and require a full-scale universal quantum computer to be tested, others have been implemented on small-scale or special purpose quantum devices.




Adaptive Motion of Animals and Machines


Book Description

• Motivation It is our dream to understand the principles of animals’ remarkable ability for adaptive motion and to transfer such abilities to a robot. Up to now, mechanisms for generation and control of stereotyped motions and adaptive motions in well-known simple environments have been formulated to some extentandsuccessfullyappliedtorobots.However,principlesofadaptationto variousenvironmentshavenotyetbeenclari?ed,andautonomousadaptation remains unsolved as a seriously di?cult problem in robotics. Apparently, the ability of animals and robots to adapt in a real world cannot be explained or realized by one single function in a control system and mechanism. That is, adaptation in motion is induced at every level from thecentralnervoussystemtothemusculoskeletalsystem.Thus,weorganized the International Symposium on Adaptive Motion in Animals and Machines(AMAM)forscientistsandengineersconcernedwithadaptation onvariouslevelstobebroughttogethertodiscussprinciplesateachleveland to investigate principles governing total systems. • History AMAM started in Montreal (Canada) in August 2000. It was organized by H. Kimura (Japan), H. Witte (Germany), G. Taga (Japan), and K. Osuka (Japan), who had agreed that having a small symposium on motion control, with people from several ?elds coming together to discuss speci?c issues, was worthwhile. Those four organizing committee members determined the scope of AMAM as follows.




Prerational Intelligence: Adaptive Behavior and Intelligent Systems Without Symbols and Logic , Volume 1, Volume 2 Prerational Intelligence: Interdisciplinary Perspectives on the Behavior of Natural and Artificial Systems, Volume 3


Book Description

The present book is the product of conferences held in Bielefeld at the Center for interdisciplinary Sturlies (ZiF) in connection with a year-long ZiF Research Group with the theme "Prerational intelligence". The premise ex plored by the research group is that traditional notions of intelligent behav ior, which form the basis for much work in artificial intelligence and cog nitive science, presuppose many basic capabilities which are not trivial, as more recent work in robotics and neuroscience has shown, and that these capabilities may be best understood as ernerging from interaction and coop eration in systems of simple agents, elements that accept inputs from and act upon their surroundings. The main focus is on the way animals and artificial systems process in formation about their surroundings in order to move and act adaptively. The analysis of the collective properties of systems of interacting agents, how ever, is a problern that occurs repeatedly in many disciplines. Therefore, contributions from a wide variety of areas have been included in order to obtain a broad overview of phenomena that demoostrate complexity arising from simple interactions or can be described as adaptive behavior arising from the collective action of groups of agents. To this end we have invited contributions on topics ranging from the development of complex structures and functions in systems ranging from cellular automata, genetic codes, and neural connectivity to social behavior and evolution. Additional contribu tions discuss traditional concepts of intelligence and adaptive behavior. 1.




Prerational Intelligence


Book Description




Computational Neuroscience


Book Description

This volume includes papers presented at the Fifth Annual Computational Neurosci ence meeting (CNS*96) held in Boston, Massachusetts, July 14 - 17, 1996. This collection includes 148 of the 234 papers presented at the meeting. Acceptance for mceting presenta tion was based on the peer review of preliminary papers originally submitted in May of 1996. The papers in this volume represent final versions of this work submitted in January of 1997. As represented by this volume, computational neuroscience continues to expand in quality, size and breadth of focus as increasing numbers of neuroscientists are taking a computational approach to understanding nervous system function. Defining computa tional neuroscience as the exploration of how brains compute, it is clear that there is al most no subject or area of modern neuroscience research that is not appropriate for computational studies. The CNS meetings as well as this volume reflect this scope and di versity.