Extending Mechanics to Minds: The Mechanical Foundations of Psychology and Economics

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Cambridge University Press, May 22, 2006 - Computers
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This book deploys the mathematical axioms of modern rational mechanics to understand minds as mechanical systems that exhibit actual, not metaphorical, forces, inertia, and motion. Using precise mental models developed in artificial intelligence the author analyzes motivation, attention, reasoning, learning, and communication in mechanical terms. These analyses provide psychology and economics with new characterizations of bounded rationality; provide mechanics with new types of materials exhibiting the constitutive kinematic and dynamic properties characteristic of different kinds of minds; and provide philosophy with a rigorous theory of hybrid systems combining discrete and continuous mechanical quantities. The resulting mechanical reintegration of the physical sciences that characterize human bodies and the mental sciences that characterize human minds opens traditional philosophical and modern computational questions to new paths of technical analysis.
 

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Contents

sort of summary characterizations But some such summaries take the
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weather one can expect that physics would have been much
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Although the theory of rational decisions provides some glue to
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years have seen attempts to understand the mind by making
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theoretical atoms underlies many ideas in empiricism and philosophy of
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quantitative laws that govern the abstract process of computing which
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xt1
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elements represents the mass itself which tradition conceives of as
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a single dimension Rotating the frame preserves the dimensionality of
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106 Force
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112 Reasoned positions
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This yields a velocity of
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for conceptspervasivein everydaydiscourse aboutpsychologyand economics
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supplying additional rules for changes of coordinates In practical
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dvw
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545 Extensions
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instantaneous global states that do not also constitute proper instantaneous
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predictions in a deterministic world With determinism in each situation
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indeed since some live without fire and not all mothers
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data through it to find the matches For other purposes
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81 What is plural discrete affective cognition?
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Even in the context of our hybrid and discrete mechanical
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one of setting out or specifying forces and masses corresponding
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Agent Interior AI
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Another path for investigation might regard reason tensors as proper
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forces Classifying external forces as body or contact usually poses
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probabilities is attractively frame independent Because the objects assigned
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small fluctuations can produce large changes in probabilities Ease of
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an alternative term for the activity of the brain or
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alternative explanations Without some stopping criterion that recognizes the
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The importance of the class of things computable by Turing
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cannot yet expect such an improvement to remove many of
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things that satisfy or fail to satisfy them When this
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About the author (2006)

Jon Doyle is SAS Institute Distinguished Professor of Computer Science at North Carolina State University, Raleigh. He received a Ph.D. in Artificial Intelligence from MIT and has held research positions at Stanford University, Carnegie Mellon University, and MIT. He is the author or coauthor of over 140 publications. His main research interests center on the foundations and practice of artificial intelligence, computation, decision theory, and logic. Prof Doyle is a Fellow of the American Association for Artificial Intelligence (AAAI). He has served as a member of the AAAI Executive Council, as chairman of ACM SIGART, as a director, president, and conference chair for Principles of Knowledge Representation and Reasoning Inc., and as a member of several editorial boards.

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