Artificial intelligence engineers have developed artifacts that succeed at tasks generally thought to require great intelligence, but have yet to mechanize the common, everyday abilities of human cognition, including its central feature: understanding. Humans understand the world, their lives, and abstract ideas in ways that other animals and engineering artifacts do not. This book examines the phenomenon of human understanding and offers an approach to understanding understanding itself. The process of understanding requires essential abilities we share with other mammals, but that are not yet available to machines. Further, it requires additional abilities that machines and humans both possess but that are absent in non-human mammals, including other primates. However, it also requires some abilities that are still unique to humans. Important among the ways humans understand is the use of non-verbal means - illustrations, diagrams, paintings, and so forth. These aid understanding by grounding abstractions in familiar perceptual abilities. This book examines the use of diagrams in the process of understanding mathematical concepts as a paradigm case of grounding the understanding one thing in terms of another.
About the Author: Robert Kendall Lindsay is Professor Emeritus at the University of Michigan and Research Professor Emeritus at the University of Michigan Medical School. He received a Bachelor of Science degree in physics from Carnegie Mellon University, a Master of Arts degree in psychology from Columbia University, and a Ph.D. from Carnegie Mellon, where his mentors were Artificial Intelligence pioneers Herbert A. Simon and Allen Newell. Later, he did postdoctoral work at Stanford University on a National Science Foundation Science Faculty Fellowship studying logic, computer science, mathematics and philosophy. He was on the faculty of the Psychology Department at The University of Texas at Austin where he established one of the first graduate programs in artificial intelligence. He has held visiting appointments at Stanford University and the University of California at Irvine. He has held research positions at the IBM Corporation Research Center and the New York State Biomedical Research Center. He has been a research consultant to the RAND Corporation, System Development Corporation, General Electric Company, Xerox Corporation Palo Alto Research Center, and Electronic Data Systems, Inc. He was an early contributor to the fields of artificial intelligence and cognitive science. He was the first computer scientist to attempt to create a machine that could understand natural language by having it construct a model of a topic from language input. He has published research on the role of imagery in cognition, natural language understanding and learning, spatial reasoning, diagrammatic reasoning, visual perceptiom, expert systems, genetic algortithms, and medical hypothesis discovery by citation analysis. Lindsay has a long-standing interest in the philosophy of science, especially the foundations of artificial intelligence and psychology, and the prospects and limitations of computational models of intelligence. He has been a student and critic of these subjects and written many reviews and analyses of books and scientific papers about psychology and computational methods.