This volume brings together leading scholars in intelligence research to present various perspectives. Each contributor builds upon past studies of intelligence and explores new ideas that differ radically from traditional notions about intelligence. Contributors also examine how intelligence changes over the lifespan, focusing on such issues as the importance of environmental context in determining intelligence and the importance of understanding how intelligence relates to other constructs like emotion and temperament.

with contributions by numerous experts

Beyond I.Q.: A Triarchic Theory of Human Intelligence contends that the influence of certain psychological factors upon intelligence is strong enough to be considered highly significant in the evaluation of I.Q. The triarchic theory of human intelligence, accordingly, reaches "beyond I.Q".

Not since the landmark publication of Handbook of Human Intelligence in 1982 has the field of intelligence been more alive than it is today. Spurred by the new developments in this rapidly expanding field, Dr Sternberg has brought together a stellar list of contributors to provide a comprehensive, broad and deeply thematic review of intelligence that will be accessible to both scholar and student. The field of intelligence is lively on many fronts, and this volume provides full coverage on topics such as behavior-genetic models, evolutionary models, cognitive models, emotional intelligence, practical intelligence, and group difference. Handbook of Intelligence is largely expanded, covering areas such as animal and artificial intelligence, as well as human intelligence. It fully reflects important theoretical progress made since the early 1980s.

This handbook is an essential, comprehensive resource for students and academics interested in topics in cognitive psychology, including perceptual issues, attention, memory, knowledge representation, language, emotional influences, judgment, problem solving, and the study of individual differences in cognition.

"This is a blockbuster of a book. It allows teachers to follow standards, but provides space for them to develop students′ wisdom, intelligence, and creativity (and of course success). Both teachers and students will come to understand themselves and their values better." —William E. Doll, Jr., Professor Emeritus Louisiana State University The essential guide for teaching beyond the test! Students with strong higher-order thinking skills are more likely to become successful, lifelong learners. Based on extensive, collaborative research by leading authorities in the field, this book shows how to implement teaching and learning strategies that nurture intelligence, creativity, and wisdom. This practical teaching manual offers an overview of the WICS model—Wisdom, Intelligence, Creativity, Synthesized—which helps teachers foster students′ capacities for effective learning and problem solving. Teachers will find examples for language arts, history, mathematics, and science in Grades K–12, as well as: Hands-on strategies for enhancing students′ memory, analytical, creative, and practical skills Guidelines on teaching and assessing for successful intelligence Details on how to apply the model in the classroom Teacher reflection sections, suggested readings, and sample planning checklists Teaching for Wisdom, Intelligence, Creativity, and Success is ideal for educators seeking to broaden their teaching repertoire as they expand the skills and abilities of students at all levels.

A comprehensive introduction to new approaches in artificial intelligence and robotics that are inspired by self-organizing biological processes and structures. New approaches to artificial intelligence spring from the idea that intelligence emerges as much from cells, bodies, and societies as it does from evolution, development, and learning. Traditionally, artificial intelligence has been concerned with reproducing the abilities of human brains; newer approaches take inspiration from a wider range of biological structures that that are capable of autonomous self-organization. Examples of these new approaches include evolutionary computation and evolutionary electronics, artificial neural networks, immune systems, biorobotics, and swarm intelligence—to mention only a few. This book offers a comprehensive introduction to the emerging field of biologically inspired artificial intelligence that can be used as an upper-level text or as a reference for researchers. Each chapter presents computational approaches inspired by a different biological system; each begins with background information about the biological system and then proceeds to develop computational models that make use of biological concepts. The chapters cover evolutionary computation and electronics; cellular systems; neural systems, including neuromorphic engineering; developmental systems; immune systems; behavioral systems—including several approaches to robotics, including behavior-based, bio-mimetic, epigenetic, and evolutionary robots; and collective systems, including swarm robotics as well as cooperative and competitive co-evolving systems. Chapters end with a concluding overview and suggested reading.