Cognitive maps, mental representations which inform thought and action, are templates for human perception and behavior. Bringing together diverse disciplines--cognitive and social psychology, biopsychology, history, physics, cosmology, chemistry, population ecology, economics, and philosophy of science--This volume comprises the revised and updated texts of the majority of papers first given at the international meeting of the General Evolution Research Group, held at the U. of Bologna, Italy in May 1989. The essays explore the development of cognitive maps from their biological and historical bases to their contemporary forms. Includes a closing commentary by Umberto Eco. Annotation copyright by Book News, Inc., Portland, OR

This important work brings together international academics from a variety of disciplines to explore the topic of spatial cognition on a 'geographic' scale. It provides an overview of the historical origins of the subject, a description of current debates and suggests directions for future research.

and processes which are exclusive to humans in their encoding, storing, decoding and retrieving spatial knowledge for various tasks. The authors present and discuss connectionist models of cognitive maps which are based on local representation, versus models which are based on distributed representation, as well as connectionist models concerning language and spatial relations. As is well known, Gibson's (1979) ecological approach suggests a view on cognition which is diametrically different from the classical main stream view: perception (and thus cognition) is direct, immediate and needs no internal information processing, and is thus essentially an external process of interaction between an organism and its external environment. The chapter by Harry Heft introduces J. J. Gibson's ecological approach and its implication to the construction of cognitive maps in general and to the issue of wayfinding in particular. According to Heft, main stream cognitive sciences are essentially Cartesian in nature and have not as yet internalized the implications of Darwin's theory of evolution. Gibson, in his ecological approach, has tried to do exactly this. The author introduces the basic terminology of the ecological approach and relates its various notions, in particular optic flow, nested hierarchy and affordances, to navigation and the way routes and places in the environment are learned.

Fuzzy Cognitive Maps (FCM) constitute cognitive models in the form of fuzzy directed graphs consisting of two basic elements: the nodes, which basically correspond to “concepts” bearing different states of activation depending on the knowledge they represent, and the “edges” denoting the causal effects that each source node exercises on the receiving concept expressed through weights. Weights take values in the interval [-1,1], which denotes the positive, negative or neutral causal relationship between two concepts. An FCM can be typically obtained through linguistic terms, inherent to fuzzy systems, but with a structure similar to the neural networks, which facilitates data processing, and has capabilities for training and adaptation. During the last 10 years, an exponential growth of published papers in FCMs was followed showing great impact potential. Different FCM structures and learning schemes have been developed, while numerous studies report their use in many contexts with highly successful modeling results. The aim of this book is to fill the existing gap in the literature concerning fundamentals, models, extensions and learning algorithms for FCMs in knowledge engineering. It comprehensively covers the state-of-the-art FCM modeling and learning methods, with algorithms, codes and software tools, and provides a set of applications that demonstrate their various usages in applied sciences and engineering.

This important edited volume is the first such book ever published on fuzzy cognitive maps (FCMs). Professor Michael Glykas has done an exceptional job in bringing together and editing its seventeen chapters. The volume appears nearly a quarter century after my original article “Fuzzy Cognitive Maps” appeared in the International Journal of Man-Machine Studies in 1986. The volume accordingly reflects many years of research effort in the development of FCM theory and applications—and portends many more decades of FCM research and applications to come. FCMs are fuzzy feedback models of causality. They combine aspects of fuzzy logic, neural networks, semantic networks, expert systems, and nonlinear dynamical systems. That rich structure endows FCMs with their own complexity and lets them apply to a wide range of problems in engineering and in the soft and hard sciences. Their partial edge connections allow a user to directly represent causality as a matter of degree and to learn new edge strengths from training data. Their directed graph structure allows forward or what-if inferencing. FCM cycles or feedback paths allow for complex nonlinear dynamics. Control of FCM nonlinear dynamics can in many cases let the user encode and decode concept patterns as fixed-point attractors or limit cycles or perhaps as more exotic dynamical equilibria. These global equilibrium patterns are often “hidden” in the nonlinear dynamics. The user will not likely see these global patterns by simply inspecting the local causal edges or nodes of large FCMs.

The field of Soft Computing in Humanities and Social Sciences is at a turning point. The strong distinction between “science” and “humanities” has been criticized from many fronts and, at the same time, an increasing cooperation between the so-called “hard sciences” and “soft sciences” is taking place in a wide range of scientific projects dealing with very complex and interdisciplinary topics. In the last fifteen years the area of Soft Computing has also experienced a gradual rapprochement to disciplines in the Humanities and Social Sciences, and also in the field of Medicine, Biology and even the Arts, a phenomenon that did not occur much in the previous years. The collection of this book presents a generous sampling of the new and burgeoning field of Soft Computing in Humanities and Social Sciences, bringing together a wide array of authors and subject matters from different disciplines. Some of the contributors of the book belong to the scientific and technical areas of Soft Computing while others come from various fields in the humanities and social sciences such as Philosophy, History, Sociology or Economics. Rudolf Seising received a Ph.D. degree in philosophy of science and a postdoctoral lecture qualification (PD) in history of science from the Ludwig Maximilians University of Munich. He is an Adjoint Researcher at the European Centre for Soft Computing in Mieres (Asturias), Spain. Veronica Sanz earned a Ph.D. in Philosophy at the University Complutense of Madrid (Spain). At the moment she is a Postdoctoral Researcher at the Science, Technology and Society Center in the University of California at Berkeley. Veronica Sanz earned a Ph.D. in Philosophy at the University Complutense of Madrid (Spain). At the moment she is a Postdoctoral Researcher at the Science, Technology and Society Center in the University of California at Berkeley.

How do animals perceive the world, learn, remember, search for food or mates, communicate, and find their way around? Do any nonhuman animals count, imitate one another, use a language, or have a culture? What are the uses of cognition in nature and how might it have evolved? What is the current status of Darwin's claim that other species share the same "mental powers" as humans, but to different degrees? In this completely revised second edition of Cognition, Evolution, and Behavior, Sara Shettleworth addresses these questions, among others, by integrating findings from psychology, behavioral ecology, and ethology in a unique and wide-ranging synthesis of theory and research on animal cognition, in the broadest sense--from species-specific adaptations of vision in fish and associative learning in rats to discussions of theory of mind in chimpanzees, dogs, and ravens. She reviews the latest research on topics such as episodic memory, metacognition, and cooperation and other-regarding behavior in animals, as well as recent theories about what makes human cognition unique. In every part of this new edition, Shettleworth incorporates findings and theoretical approaches that have emerged since the first edition was published in 1998. The chapters are now organized into three sections: Fundamental Mechanisms (perception, learning, categorization, memory), Physical Cognition (space, time, number, physical causation), and Social Cognition (social knowledge, social learning, communication). Shettleworth has also added new chapters on evolution and the brain and on numerical cognition, and a new chapter on physical causation that integrates theories of instrumental behavior with discussions of foraging, planning, and tool using.

This book constitutes the refereed proceedings of the 11th International Conference on Simulated Evolution and Learning, SEAL 2017, held in Shenzhen, China, in November 2017. The 85 papers presented in this volume were carefully reviewed and selected from 145 submissions. They were organized in topical sections named: evolutionary optimisation; evolutionary multiobjective optimisation; evolutionary machine learning; theoretical developments; feature selection and dimensionality reduction; dynamic and uncertain environments; real-world applications; adaptive systems; and swarm intelligence.

This book updates the Dual Coding Theory of mind (DCT), a theory of modern human cognition consisting of separate but interconnected nonverbal and verbal systems. Allan Paivio, a leading scholar in cognitive psychology, presents this masterwork as new findings in psychological research on memory, thought, language, and other core areas have flourished, as have pioneering developments in the cognitive neurosciences. Mind and Its Evolution provides a thorough exploration into how these adaptive nonverbal and verbal systems might have evolved, as well as a careful comparison of DCT with contrasting "single-code" cognitive theories. Divided into four parts, this text begins with a general, systematic theory of modern human cognition as the reference model for interpreting the cognitive abilities of evolutionary ancestors. The first half of the book discusses mind as it is; the second half addresses how it came to be that way. Each half is subdivided into two parts defined by thematic chapters. Mind and Its Evolution concludes with evidence-based suggestions about nourishing mental growth through applications of DCT in education, psychotherapy, and health. This volume will appeal to cognitive and evolutionary psychologists, as well as students in the areas of memory, language, cognition, and mind evolution specialists in psychology, philosophy, and other disciplines.