Social insects--ants, bees, termites, and wasps--can be viewed as powerful problem-solving systems with sophisticated collective intelligence. Composed of simple interacting agents, this intelligence lies in the networks of interactions among individuals and between individuals and the environment. A fascinating subject, social insects are also a powerful metaphor for artificial intelligence, and the problems they solve--finding food, dividing labor among nestmates, building nests, responding to external challenges--have important counterparts in engineering and computer science.

This...

Social insects--ants, bees, termites, and wasps--can be viewed as powerful problem-solving systems with sophisticated collective intelligence. Composed of simple interacting agents, this intelligence lies in the networks of interactions among individuals and between individuals and the environment. A fascinating subject, social insects are also a powerful metaphor for artificial intelligence, and the problems they solve--finding food, dividing labor among nestmates, building nests, responding to external challenges--have important counterparts in engineering and computer science.

This...

As part of the SFI series, this book presents the most up-to-date research in the study of human and primate societies, presenting recent advances in software and algorithms for modeling societies. It also addresses case studies that have applied agent-based modeling approaches in archaeology, cultural anthropology, primatology, and sociology. Many things set this book apart from any other on modeling in the social sciences, including the emphasis on small-scale societies and the attempts to maximize realism in the modeling efforts applied to social problems and questions. It is an ideal book...

This volume presents a set of coherent, cross-referenced perspectives on incorporating the spatial representation and analytical power of GIS with agent-based modelling of evolutionary and non-linear processes and phenomena. Many recent advances in software algorithms for incorporating geographic data in modeling social and ecological behaviors, and successes in applying such algorithms, had not been adequately reported in the literature. This book seeks to serve as the standard guide to this broad area.

This volume presents a set of coherent, cross-referenced perspectives on incorporating the spatial representation andanalytical power of GIS with agent-based modelling of evolutionary and non-linear processes and phenomena. Many recent advances in software algorithms for incorporating geographic data in modeling social and ecological behaviors, and successes in applying such algorithms, had not been adequately reported in the literature. This book seeks to serve as the standard guide to this broad area.

This book is a collection of essays exploring adaptive systems from many perspectives, ranging from computational applications to models of adaptation in living and social systems. The essays on computation discuss history, theory, applications, and possible threats of adaptive and evolving computations systems. The modeling chapters cover topics such as evolution in microbial populations, the evolution of cooperation, and how ideas about evolution relate to economics.
The title Perspectives on Adaptation in Natural and Artificial Systems honors John Holland, whose 1975 Book,...

These lectures develop simple models of complex social processes using nonlinear dynamics and mathematical biology. Dynamical analogies between seemingly disparate social and biological phenomena--revolutions and epidemics, arms races, and ecosystem dynamics--are revealed and exploited. Nonlinear Dynamics, Mathematical Biology, and Social Science invites social scientists to relax--in some cases abandon--the predominant assumption of perfectly informed utility maximization and explore social dynamics from such perspectives as epidemiology and predator-prey theory. The volume includes a...

This book is a comprehensive introduction to the neural network models currently under intensive study for computational applications. It is a detailed, logically-developed treatment that covers the theory and uses of collective computational networks, including associative memory, feed forward networks, and unsupervised learning. It also provides coverage of neural network applications in a variety of problems of both theoretical and practical interest.

"No science has ever been done without an indissoluble link between theory and fact: facts are colored by the theoretical spectacles on puts on, just as much as theory is shaped by the results of empir"

This book explores not only the connections between quantum and classical physics, information and its transfer, computation, and their significance for the formulation of physical theories, but it also considers the origins evolution of the information-processing entities, their complexity, and the manner in which they analyze their perceptions to form models of the Universe.