This volume describes our intellectual path from the physics of complex sys tems to the science of artificial cognitive systems. It was exciting to discover that many of the concepts and methods which succeed in describing the self organizing phenomena of the physical world are relevant also for understand ing cognitive processes. Several nonlinear physicists have felt the fascination of such discovery in recent years. In this volume, we will limit our discussion to artificial cognitive systems, without attempting to model either the cognitive behaviour or the nervous structure of humans or animals. On the one hand, such artificial systems are important per se; on the other hand, it can be expected that their study will shed light on some general principles which are relevant also to biological cognitive systems. The main purpose of this volume is to show that nonlinear dynamical systems have several properties which make them particularly attractive for reaching some of the goals of artificial intelligence. The enthusiasm which was mentioned above must however be qualified by a critical consideration of the limitations of the dynamical systems approach. Understanding cognitive processes is a tremendous scientific challenge, and the achievements reached so far allow no single method to claim that it is the only valid one. In particular, the approach based upon nonlinear dynamical systems, which is our main topic, is still in an early stage of development.

This book presents a new approach that can be applied to complex, integrated individual and social human processes. It provides an alternative means of addressing complexity, better suited for its purpose than and effectively complementing traditional strategies involving isolation and separation assumptions. Network-oriented modeling allows high-level cognitive, affective and social models in the form of (cyclic) graphs to be constructed, which can be automatically transformed into executable simulation models. The modeling format used makes it easy to take into account theories and findings about complex cognitive and social processes, which often involve dynamics based on interrelating cycles. Accordingly, it makes it possible to address complex phenomena such as the integration of emotions within cognitive processes of all kinds, of internal simulations of the mental processes of others, and of social phenomena such as shared understandings and collective actions. A variety of sample models – including those for ownership of actions, fear and dreaming, the integration of emotions in joint decision-making based on empathic understanding, and evolving social networks – illustrate the potential of the approach. Dedicated software is available to support building models in a conceptual or graphical manner, transforming them into an executable format and performing simulation experiments. The majority of the material presented has been used and positively evaluated by undergraduate and graduate students and researchers in the cognitive, social and AI domains. Given its detailed coverage, the book is ideally suited as an introduction for graduate and undergraduate students in many different multidisciplinary fields involving cognitive, affective, social, biological, and neuroscience domains.

An introduction to the application of dynamical systems science to the cognitive sciences. Dynamical Cognitive Science makes available to the cognitive science community the analytical tools and techniques of dynamical systems science, adding the variables of change and time to the study of human cognition. The unifying theme is that human behavior is an "unfolding in time" whose study should be augmented by the application of time-sensitive tools from disciplines such as physics, mathematics, and economics, where change over time is of central importance. The book provides a fast-paced, comprehensive introduction to the application of dynamical systems science to the cognitive sciences. Topics include linear and nonlinear time series analysis, chaos theory, complexity theory, relaxation oscillators, and metatheoretical issues of modeling and theory building. Tools and techniques are discussed in the context of their application to basic cognitive science problems, including perception, memory, psychophysics, judgment and decision making, and consciousness. The final chapter summarizes the contemporary study of consciousness and suggests how dynamical approaches to cognitive science can help to advance our understanding of this central concept.

In Complexity and Postmodernism, Paul Cilliers explores the idea of complexity in the light of contemporary perspectives from philosophy and science. Cilliers offers us a unique approach to understanding complexity and computational theory by integrating postmodern theory (like that of Derrida and Lyotard) into his discussion. Complexity and Postmodernism is an exciting and an original book that should be read by anyone interested in gaining a fresh understanding of complexity, postmodernism and connectionism.

Human-System interaction has been and will continue to be of interest to many researchers of various disciplines: engineers, computer scientists, psychologists, and social scientists. The research in Human-System Interaction (HSI) has progressed from the era of using anthropomorphic data to design workspace to the current period which utilizes human and artificial sensors to design sensory-based cooperative workspace. In either of these developments, HSI has been known to be complex. In 1994, we initiated a series of symposiums on Human Interaction with Complex Systems. It was then that various ideas surrounding HSI for today and tomorrow were discussed by many scientists in the related disciplines. As a follow-up, in 1995 the Second Symposium was organized. The objective of this symposium was to attempt to defme a framework, principles, and theories for HSI research. This book is the result of that symposium. The 1995 symposium brought together a number of experts in the area of HSI. The symposium was more focused on expert opinions and testimonies than traditional meetings for technical papers. There were three reasons for that approach.

The widespread interest this book has found among professors, scientists and stu dents working in a variety of fields has made a new edition necessary. I have used this opportunity to add three new chapters on recent developments. One of the most fascinating fields of modern science is cognitive science which has become a meet ing place of many disciplines ranging from mathematics over physics and computer science to psychology. Here, one of the important links between these fields is the concept of information which, however, appears in various disguises, be it as Shan non information or as semantic information (or as something still different). So far, meaning seemed to be exorcised from Shannon information, whereas meaning plays a central role in semantic (or as it is sometimes called "pragmatic") information. In the new chapter 13 it will be shown, however, that there is an important interplay between Shannon and semantic information and that, in particular, the latter plays a decisive role in the fixation of Shannon information and, in cognitive processes, al lows a drastic reduction of that information. A second, equally fascinating and rapidly developing field for mathematicians, computer scientists and physicists is quantum information and quantum computa tion. The inclusion of these topics is a must for any modern treatise dealing with in formation. It becomes more and more evident that the abstract concept of informa tion is inseparably tied up with its realizations in the physical world.

In terms of simple and complex systems, it is a whole new world out there. At the initial publication of this book, fourteen years ago, the web was in its infancy, DVDs did not exist, cell phones were few and far between, and the information superhighway was just a blip upon the horizon. If you used the terms "social engineering," you were most likely a political scientist, and if you were "phishing" you might be listening to a rock band. The second edition of a bestseller, Human Factors in Simple and Complex Systems provides the necessary understanding of the breadth and depth of human factors issues that influence the design, implementation, and evaluation of products and systems. Emphasizing the close relationship between basic theory and application, the authors delineate a framework for the research process, present an integrated view of the current state of knowledge, and examine how these factors can be applied to system design. The new edition addresses such concepts as situation awareness and highlights topics of interest, with a special focus on computer applications and human-computer interaction. See what’s new in the Second Edition New topics, such as situational awareness, that capture the tremendous changes in human factors and ergonomics Tightly integrates basic research and application, strengthening the link between knowledge and practice Each chapter includes a separate box that discusses a topic of current interest related to human interaction with computers and recent technology Demonstrating a general approach to solving a broad range of system problems, the book provides coverage of the theoretical foundation on which the discipline of human factors is built. Structured around human information processing, it covers the full range of contemporary human factors and ergonomics, then shows you how to apply them.