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Nobel Laureate Herbert A. Simon has in the past quarter century been in the front line of the information-processing revolution; in fact, to a remarkable extent his and his colleagues' contributions have written the history of that revolution in cognitive psychology. Research in this burgeoning new branch of knowledge seeks to describe with precision the workings of the human mind in terms of a small number of basic mechanisms organized into strategies. Newly developed computer languages express theories of mental processes, so that computers can then simulate the predicted human behavior. This book brings together papers dating from the start of Simon's career to the present. Its focus is on modeling the chief components of human cognition and on testing these models experimentally. After considering basic structural elements of the human information-processing system (especially search, selective attention, and storage in memory), Simon builds from these components a system capable of solving problems, inducing rules and concepts, perceiving, and understanding. These essays describe a relatively austere, simple, and unified processing system capable of highly complex and various tasks. They provide strong evidence for an explanation of human thinking in terms of basic information processes.
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.
A multidisciplinary collaboration exploring the role of cultural knowledge in everyday language and understanding.
This book stresses the interrelatedness of knowledge by extricating models that cut across traditional disciplinary boundaries. For example, science can find models from the technology and semantic field of music, music can find its models from the technology and semantic field of science, and each domain may be guided by a philosophical or metaphysical principle - thus, the title of the book. But the book itself is structured as a mirror image of its title. Chapters 1-6 provide instances of the role of music in such domains as epistemology and logic, as well as in the early modern sciences of developmental biology, continuum mechanics, anatomy and physiological psychology, whereas Chapters 7-10 provide instances of what some other domains of knowledge have given back to the philosophy and theory of music.
Essays that pay tribute to the wide-ranging influence of the late Herbert Simon, by friends and colleagues. Herbert Simon (1916-2001), in the course of a long and distinguished career in the social and behavioral sciences, made lasting contributions to many disciplines, including economics, psychology, computer science, and artificial intelligence. In 1978 he was awarded the Nobel Prize in economics for his research into the decision-making process within economic organizations. His well-known book The Sciences of the Artificial addresses the implications of the decision-making and problem-solving processes for the social sciences. This book (the title is a variation on the title of Simon's autobiography, Models of My Life) is a collection of short essays, all original, by colleagues from many fields who felt Simon's influence and mourn his loss. Mixing reminiscence and analysis, the book represents "a small acknowledgment of a large debt." Each of the more than forty contributors was asked to write about the one work by Simon that he or she had found most influential. The editors then grouped the essays into four sections: "Modeling Man," "Organizations and Administration," "Modeling Systems," and "Minds and Machines." The contributors include such prominent figures as Kenneth Arrow, William Baumol, William Cooper, Gerd Gigerenzer, Daniel Kahneman, David Klahr, Franco Modigliani, Paul Samuelson, and Vernon Smith. Although they consider topics as disparate as "Is Bounded Rationality Unboundedly Rational?" and "Personal Recollections from 15 Years of Monthly Meetings," each essay is a testament to the legacy of Herbert Simon—to see the unity rather than the divergences among disciplines.
The human brain is made up of 85 billion neurons, which are connected by over 100 trillion synapses. For more than a century, a diverse array of researchers searched for a language that could be used to capture the essence of what these neurons do and how they communicate – and how those communications create thoughts, perceptions and actions. The language they were looking for was mathematics, and we would not be able to understand the brain as we do today without it. In Models of the Mind, author and computational neuroscientist Grace Lindsay explains how mathematical models have allowed scientists to understand and describe many of the brain's processes, including decision-making, sensory processing, quantifying memory, and more. She introduces readers to the most important concepts in modern neuroscience, and highlights the tensions that arise when the abstract world of mathematical modelling collides with the messy details of biology. Each chapter of Models of the Mind focuses on mathematical tools that have been applied in a particular area of neuroscience, progressing from the simplest building block of the brain – the individual neuron – through to circuits of interacting neurons, whole brain areas and even the behaviours that brains command. In addition, Grace examines the history of the field, starting with experiments done on frog legs in the late eighteenth century and building to the large models of artificial neural networks that form the basis of modern artificial intelligence. Throughout, she reveals the value of using the elegant language of mathematics to describe the machinery of neuroscience.
The volume offers a number of representative papers on cognitive models that are invoked when people deal with questions of social identity, political and economic manipulation, and more general issues such as the genomic discourse. In line with the well-known volume Cultural Models in Language and Thought by Holland and Quinn (1987), the volume shows that Cognitive Linguistics has further explored the idea that we think about social reality in terms of models - 'cognitive/cultural models' or 'folk theories'. As in cultural models, the present volume demonstrates that the technical apparatus of Cognitive Linguistics can be used to analyze the various ways our conception of social reality is shaped by underlying cognitive and/or cultural models or patterns of thought, and also looks into how this is done. The new inroad the volume wants to pursue is the deliberate and explicit orientation towards a cognitive sociolinguistics, or more generally, a cognitive semiotics.
Work with data like a pro using this guide that breaks down how to organize, apply, and most importantly, understand what you are analyzing in order to become a true data ninja. From the stock market to genomics laboratories, census figures to marketing email blasts, we are awash with data. But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren't enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page shows us the mathematical, statistical, and computational models—from linear regression to random walks and far beyond—that can turn anyone into a genius. At the core of the book is Page's "many-model paradigm," which shows the reader how to apply multiple models to organize the data, leading to wiser choices, more accurate predictions, and more robust designs. The Model Thinker provides a toolkit for business people, students, scientists, pollsters, and bloggers to make them better, clearer thinkers, able to leverage data and information to their advantage.
In this candid and witty autobiography, Nobel laureate Herbert A. Simon looks at his distinguished and varied career, continually asking himself whether (and how) what he learned as a scientist helps to explain other aspects of his life. A brilliant polymath in an age of increasing specialization, Simon is one of those rare scholars whose work defines fields of inquiry. Crossing disciplinary lines in half a dozen fields, Simon's story encompasses an explosion in the information sciences, the transformation of psychology by the information-processing paradigm, and the use of computer simulation for modeling the behavior of highly complex systems. Simon's theory of bounded rationality led to a Nobel Prize in economics, and his work on building machines that think—based on the notion that human intelligence is the rule-governed manipulation of symbols—laid conceptual foundations for the new cognitive science. Subsequently, contrasting metaphors of the maze (Simon's view) and of the mind (neural nets) have dominated the artificial intelligence debate. There is also a warm account of his successful marriage and of an unconsummated love affair, letters to his children, columns, a short story, and political and personal intrigue in academe.