This volume focuses on the modeling of cognition, and brings together contributions from psychologists and researchers in the field of cognitive science. The shared platform of this work is to advocate a dynamical systems approach to cognition. Several aspects of this approach are considered here: chaos theory, artificial intelligence and Alife models, catastrophe theory and, most importantly, self-organization theory or synergetics. The application of nonlinear systems theory to cognitive science in general, and to cognitive psychology in particular, is a growing field that has gained further momentum thanks to new contributions from the science of robotics. The recent development in cognitive science towards an account of embodiment, together with the general approach of complexity theory and dynamics, will have a major impact on our psychological understanding of reasoning, thinking and behavior.

This volume focuses on the modeling of cognition, and brings together contributions from psychologists and researchers in the field of cognitive science. The shared platform of this work is to advocate a dynamical systems approach to cognition. Several aspects of this approach are considered here: chaos theory, artificial intelligence and Alfie models, catastrophe theory and, most importantly, self-organization theory or synergetics. The application of nonlinear systems theory to cognitive science in general, and to cognitive psychology in particular, is a growing field that has gained further momentum thanks to new contributions from the science of robotics. The recent development in cognitive science towards an account of embodiment, together with the general approach of complexity theory and dynamics, will have a major impact on our psychological understanding of reasoning, thinking and behavior.

The shared platform of the articles collected in this volume is usedto advocate a dynamical systems approach to cognition. It is arguedthat recent developments in cognitive science towards an account ofembodiment, together with the general approach of complexity theoryand dynamics, have a major impact on behavioral and cognitivescience.

The shared platform of the articles collected in this volume is used to advocate a dynamical systems approach to cognition. It is argued that recent developments in cognitive science towards an account of embodiment, together with the general approach of complexity theory and dynamics, have a major impact on behavioral and cognitive science. The book points out that there are two domains that follow naturally from the stance of embodiment: first, coordination dynamics is an established empirical paradigm that is best able to aid the approach; second, the obvious goal-directedness of intelligent action (i.e., intentionality) is nicely addressed in the framework of the dynamical synergetic approach.

At the start of the new millennium, mankind is challenged by a paradox: the more we know about the world the more uncertain we become in understanding and predicting how it works. This book presents an outline of a new basis for Systems Science, and a methodology for its application in complex environmental, economic, social, and technological systems.

The Mind and Brain are usually considered as one and the same nonlinear, complex dynamical system, in which information processing can be described with vector and tensor transformations and with attractors in multidimensional state spaces. Thus, an internal neurocognitive representation concept consists of a dynamical process which filters out statistical prototypes from the sensorial information in terms of coherent and adaptive n-dimensional vector fields. These prototypes serve as a basis for dynamic, probabilistic predictions or probabilistic hypotheses on prospective new data (see the recently introduced approach of "predictive coding" in neurophilosophy). Furthermore, the phenomenon of sensory and language cognition would thus be based on a multitude of self-regulatory complex dynamics of synchronous self-organization mechanisms, in other words, an emergent "flux equilibrium process" ("steady state") of the total collective and coherent neural activity resulting from the oscillatory actions of neuronal assemblies. In perception it is shown how sensory object informations, like the object color or the object form, can be dynamically related together or can be integrated to a neurally based representation of this perceptual object by means of a synchronization mechanism ("feature binding"). In language processing it is shown how semantic concepts and syntactic roles can be dynamically related together or can be integrated to neurally based systematic and compositional connectionist representations by means of a synchronization mechanism ("variable binding") solving the Fodor-Pylyshyn-Challenge. Since the systemtheoretical connectionism has succeeded in modeling the sensory objects in perception as well as systematic and compositional representations in language processing with this vector- and oscillation-based representation format, a new, convincing theory of neurocognition has been developed, which bridges the neuronal and the cognitive analysis level. The book describes how elementary neuronal information is combined in perception and language, so it becomes clear how the brain processes this information to enable basic cognitive performance of the humans.

Provides an accessible introduction to computational complexity analysis and its application to questions of intractability in cognitive science.