This volume collects together peer reviewed versions of most of the papers presented at the Ninth Neural Computation and Psychology Workshop (NCPW9), held in 2004 at the University of Plymouth (England). The conference invited submissions on neural computation models of all cognitive and psychological processes. The special theme of this year's workshop was “Modeling of Language, Cognition and Action. This topic had the aim to extend the conference appeal from the connectionist psychology community to leaders in neuroscience, robotics and cognitive systems design.The chapters cover the breadth of research in neural computation and psychology, with numerous papers that focus on language modeling, this year's special theme. The book includes chapters from internationally renowned researchers in the various fields of cognitive psychology (such as Art Glenberg and Jonathan Evans) as well as computer science and robotics (such as Stefan Wermter & Stefano Nolfi).The proceedings have been selected for coverage in:• Neuroscience Citation Index®• Index to Scientific & Technical Proceedings® (ISTP® / ISI Proceedings)• Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings)• Index to Social Sciences & Humanities Proceedings® (ISSHP® / ISI Proceedings)• Index to Social Sciences & Humanities Proceedings (ISSHP CDROM version / ISI Proceedings)• CC Proceedings — Engineering & Physical Sciences• CC Proceedings — Biomedical, Biological & Agricultural Sciences

The neural computational approach to cognitive and psychological processes is relatively new. However, Neural Computation and Psychology Workshops (NCPW), first held 16 years ago, lie at the heart of this fast-moving discipline, thanks to its interdisciplinary nature OCo bringing together researchers from different disciplines such as artificial intelligence, cognitive science, computer science, neurobiology, philosophy and psychology to discuss their work on models of cognitive processes."

Interdisciplinary Handbook of Perceptual Control Theory Volume II: Living in the Loop brings together the latest research, theory, and applications from W. T. Powers' Perceptual Control Theory (PCT) that proposes that the behavior of a living organism lies in the control of perceived aspects of both itself and its environment. Sections cover theory, the application of PCT to a broad range of disciplines, why perceptual control is fundamental to understanding human nature, a new way to do research on brain processes and behavior, how the role of natural selection in behavior can be demystified, how engineers can emulate human purposeful behavior in robots, and much more. Each chapter includes an author biography to set the context of their work within the development of PCT. - Presents case studies that show how PCT can be applied in different disciplines - Illustrates the Test for the Controlled Variable (TCV) and the construction of functional models as fruitful alternatives to mainstream experimental design when studying behavior - Shows how theory illuminates structure and functions in brain anatomy - Compares and contrasts PCT with other contemporary, interdisciplinary theories

This book is for both robot builders and scientists who study human behaviour and human societies. Scientists do not only collect empirical data but they also formulate theories to explain the data. Theories of human behaviour and human societies are traditionally expressed in words but, today, with the advent of the computer they can also be expressed by constructing computer-based artefacts. If the artefacts do what human beings do, the theory/blueprint that has been used to construct the artefacts explains human behaviour and human societies. Since human beings are primarily bodies, the artefacts must be robots, and human robots must progressively reproduce all we know about human beings and their societies. And, although they are purely scientific tools, they can have one very important practical application: helping human beings to better understand the many difficult problems they face today and will face in the future - and, perhaps, to find solutions for these problems.

This book is a continuation of our previous volumes on Innovations in Defence Support Systems. This book includes a sample of recent advances in intelligent monitoring. The contributions include: · Data fusion in modern surveillance · Distributed intelligent surveillance systems modeling for performance evaluation · Incremental learning on trajectory clustering · Pedestrian speed profiles from video sequence · System-wide tracking of individuals · A scalable approach based on normality components for intelligent surveillance · Distributed camera overlap estimation · Multi-robot team for environmental monitoring The book is directed to the security experts, engineers, scientists, students and professors who are interested in intelligent monitoring.

Arguments over the developmental origins of human knowledge are ancient, founded in the writings of Plato, Aristotle, Descartes, Hume, and Kant. They have also persisted long enough to become a core area of inquiry in cognitive and developmental science. Empirical contributions to these debates, however, appeared only in the last century, when Jean Piaget offered the first viable theory of knowledge acquisition that centered on the great themes discussed by Kant: object, space, time, and causality. The essence of Piaget's theory is constructivism: The building of concepts from simpler perceptual and cognitive precursors, in particular from experience gained through manual behaviors and observation. The constructivist view was disputed by a generation of researchers dedicated to the idea of the "competent infant," endowed with knowledge (say, of permanent objects) that emerged prior to facile manual behaviors. Taking this possibility further, it has been proposed that many fundamental cognitive mechanisms -- reasoning, event prediction, decision-making, hypothesis testing, and deduction -- operate independently of all experience, and are, in this sense, innate. The competent-infant view has an intuitive appeal, attested to by its widespread popularity, and it enjoys a kind of parsimony: It avoids the supposed philosophical pitfall posed by having to account for novel forms of knowledge in inductive learners. But this view leaves unaddressed a vital challenge: to understand the mechanisms by which new knowledge arises. This challenge has now been met. The neoconstructivist approach is rooted in Piaget's constructivist emphasis on developmental mechanisms, yet also reflects modern advances in our understanding of learning mechanisms, cortical development, and modeling. This book brings together, for the first time, theoretical views that embrace computational models and developmental neurobiology, and emphasize the interplay of time, experience, and cortical architecture to explain emergent knowledge, with an empirical line of research identifying a set of general-purpose sensory, perceptual, and learning mechanisms that guide knowledge acquisition across different domains and through development.

This book constitutes the refereed proceedings of the 4th International Conference on Artificial General Intelligence, AGI 2011, held in Mountain View, CA, USA, in August 2011. The 28 revised full papers and 26 short papers were carefully reviewed and selected from 103 submissions. The papers are written by leading academic and industry researchers involved in scientific and engineering work and focus on the creation of AI systems possessing general intelligence at the human level and beyond.

This book is the integrated presentation of a large body of work on understanding the operation of biological brains as systems. The work has been carried out by the author over the last 22 years, and leads to a claim that it is relatively straightforward to understand how human cognition results from and is supported by physiological processes in the brain. This claim has roots in the technology for designing and manufacturing electronic systems which manage extremely complex telecommunications networks with high reliability, in real time and with no human intervention. Such systems perform very large numbers of interacting control features. Although there is little direct resemblance between such systems and biological brains, the ways in which these practical considerations force system architectures within some specific bounds leads to an understanding of how different but analogous practical considerations constrain the architectures of brains within different bounds called the Recommendation Architecture. These architectural bounds make it possible to relate cognitive phenomena to physiological processes.

Our species has been a maker and user of tools for over two million years, but "cognitive technology" began with language. Cognition is thinking, and thinking has been "distributed" for at least the two hundred millennia that we have been using speech to interact and collaborate, allowing us to do collectively far more than any of us could have done individually. The invention of writing six millennia ago and print six centuries ago has distributed cognition still more widely and quickly, among people as well as their texts. But in recent decades something radically new has been happening: Advanced cognitive technologies, especially computers and the Worldwide Web, are beginning to redistribute cognition in unprecedented ways, not only among people and static texts, but among people and dynamical machines. This not only makes possible new forms of human collaboration, but new forms of cognition. This book examines the nature and prospects of distributed cognition, providing a conceptual framework for understanding it, and showcasing case studies of its development. This volume was originally published as a Special Issue of Pragmatics & Cognition (14:2, 2006).