A Model for Intelligence


Book Description

with contributions by numerous experts




Models of Intelligence


Book Description

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.




Beyond IQ


Book Description

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".




The Nature of Human Intelligence


Book Description

Provides an overview of leading scholars' approaches to understanding the nature of intelligence, its measurement, its investigation, and its development.




A Thousand Brains


Book Description

A bestselling author, neuroscientist, and computer engineer unveils a theory of intelligence that will revolutionize our understanding of the brain and the future of AI. For all of neuroscience's advances, we've made little progress on its biggest question: How do simple cells in the brain create intelligence? Jeff Hawkins and his team discovered that the brain uses maplike structures to build a model of the world—not just one model, but hundreds of thousands of models of everything we know. This discovery allows Hawkins to answer important questions about how we perceive the world, why we have a sense of self, and the origin of high-level thought. A Thousand Brains heralds a revolution in the understanding of intelligence. It is a big-think book, in every sense of the word. One of the Financial Times' Best Books of 2021 One of Bill Gates' Five Favorite Books of 2021




The Great Mental Models, Volume 1


Book Description

Discover the essential thinking tools you’ve been missing with The Great Mental Models series by Shane Parrish, New York Times bestselling author and the mind behind the acclaimed Farnam Street blog and “The Knowledge Project” podcast. This first book in the series is your guide to learning the crucial thinking tools nobody ever taught you. Time and time again, great thinkers such as Charlie Munger and Warren Buffett have credited their success to mental models–representations of how something works that can scale onto other fields. Mastering a small number of mental models enables you to rapidly grasp new information, identify patterns others miss, and avoid the common mistakes that hold people back. The Great Mental Models: Volume 1, General Thinking Concepts shows you how making a few tiny changes in the way you think can deliver big results. Drawing on examples from history, business, art, and science, this book details nine of the most versatile, all-purpose mental models you can use right away to improve your decision making and productivity. This book will teach you how to: Avoid blind spots when looking at problems. Find non-obvious solutions. Anticipate and achieve desired outcomes. Play to your strengths, avoid your weaknesses, … and more. The Great Mental Models series demystifies once elusive concepts and illuminates rich knowledge that traditional education overlooks. This series is the most comprehensive and accessible guide on using mental models to better understand our world, solve problems, and gain an advantage.







Handbook of Understanding and Measuring Intelligence


Book Description

In the Handbook of Understanding and Measuring Intelligence distinguished scholars Oliver Wilhelm and Randall W. Engle have assembled a group of respected experts from two fields of intelligence research--cognition and methods--to summarize, review, and evaluate research in their areas of expertise. Each chapter presents the state-of-the-art in a particular domain of intelligence research, illustrating and highlighting important methodological considerations, theoretical claims, and pervasive problems in the field.




The Cambridge Handbook of Intelligence and Cognitive Neuroscience


Book Description

This handbook introduces the reader to the thought-provoking research on the neural foundations of human intelligence. Written for undergraduate or graduate students, practitioners, and researchers in psychology, cognitive neuroscience, and related fields, the chapters summarize research emerging from the rapidly developing neuroscience literature on human intelligence. The volume focusses on theoretical innovation and recent advances in the measurement, modelling, and characterization of the neurobiology of intelligence differences, especially from brain imaging studies. It summarizes fundamental issues in the characterization and measurement of general intelligence, and surveys multidisciplinary research consortia and large-scale data repositories for the study of general intelligence. A systematic review of neuroimaging methods for studying intelligence is provided, including structural and diffusion-weighted MRI techniques, functional MRI methods, and spectroscopic imaging of metabolic markers of intelligence.




Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions


Book Description

One of the goals of artificial intelligence (AI) is creating autonomous agents that must make decisions based on uncertain and incomplete information. The goal is to design rational agents that must take the best action given the information available and their goals. Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions provides an introduction to different types of decision theory techniques, including MDPs, POMDPs, Influence Diagrams, and Reinforcement Learning, and illustrates their application in artificial intelligence. This book provides insights into the advantages and challenges of using decision theory models for developing intelligent systems.