Classic analysis of the subject and the development of personal probability; one of the greatest controversies in modern statistcal thought.

The now-classic Metaphors We Live By changed our understanding of metaphor and its role in language and the mind. Metaphor, the authors explain, is a fundamental mechanism of mind, one that allows us to use what we know about our physical and social experience to provide understanding of countless other subjects. Because such metaphors structure our most basic understandings of our experience, they are "metaphors we live by"--metaphors that can shape our perceptions and actions without our ever noticing them. In (...) this updated edition of Lakoff and Johnson's influential book, the authors supply an afterword surveying how their theory of metaphor has developed within the cognitive sciences to become central to the contemporary understanding of how we think and how we express our thoughts in language. (shrink)

Knowledge in a Social World offers a philosophy for the information age. Alvin Goldman explores new frontiers by creating a thoroughgoing social epistemology, moving beyond the traditional focus on solitary knowers. Against the tides of postmodernism and social constructionism Goldman defends the integrity of truth and shows how to promote it by well-designed forms of social interaction. From science to education, from law to democracy, he shows why and how public institutions should seek knowledge-enhancing practices. The result is a bold, (...) timely, and systematic treatment of the philosophical foundations of an information society. (shrink)

In this book, Newell makes the case for unified theories by setting forth a candidate.

Here the author of How to Solve It explains how to become a "good guesser." Marked by G. Polya's simple, energetic prose and use of clever examples from a wide range of human activities, this two-volume work explores techniques of guessing, inductive reasoning, and reasoning by analogy, and the role they play in the most rigorous of deductive disciplines.

This book was first published in 1984, as the revised edition of a 1979 original. The text is composed of studies in a descending sequence from perfect rationality, through imperfect and problematical rationality, to irrationality. Specifically human rationality is characterized by its capacity to relate strategically to the future, in contrast to the myopic 'gradient climbing' of natural selection. There is trenchant analysis of some of the parallels proposed in this connection between the biological and the social sciences. In the (...) chapter on imperfect rationality the crucial notion is that of 'binding oneself', as Ulysses did before setting out to the Sirens, when weakness of will may prevent us from using our capacity for perfect rationality. The second half of the book deals with rational-actor theory, comparing its logical power and success to rival approaches, and with the varieties of irrationality expressed in contradictory beliefs and desires. (shrink)

I argue that explanation should be thought of as the phenomenological mark of the operation of a particular kind of cognitive system, the theory-formation system. The theory-formation system operates most clearly in children and scientists but is also part of our everyday cognition. The system is devoted to uncovering the underlying causal structure of the world. Since this process often involves active intervention in the world, in the case of systematic experiment in scientists, and play in children, the cognitive system (...) is accompanied by a theory drive, a motivational system that impels us to interpret new evidence in terms of existing theories and change our theories in the light of new evidence. What we usually think of as explanation is the phenomenological state that accompanies the satisfaction of this drive. However, the relation between the phenomenology and the cognitive system is contingent, as in similar cases of sexual and visual phenomenology. Distinctive explanatory phenomenology may also help us to identify when the theory-formation system is operating. (shrink)

I argue that psychologists interested in human causal judgment should understand and adopt a representation of causal mechanisms by directed graphs that encode conditional independence (screening off) relations. I illustrate the benefits of that representation, now widely used in computer science and increasingly in statistics, by (i) showing that a dispute in psychology between ‘mechanist’ and ‘associationist’ psychological theories of causation rests on a false and confused dichotomy; (ii) showing that a recent, much-cited experiment, purporting to show that human subjects, (...) incorrectly let large causes ‘overshadow’ small causes, misrepresents the most likely, and warranted, causal explanation available to the subjects, in the light of which their responses were normative; (iii) showing how a recent psychological theory (due to P. Cheng) of human judgment of causal power can be considerably generalized: and (iv) suggesting a range of possible experiments comparing human and computer abilities to extract causal information from associations. (shrink)

This is a book about how we see: the environment around us (its surfaces, their layout, and their colors and textures); where we are in the environment; whether or not we are moving and, if we are, where we are going; what things are good for; how to do things (to thread a needle or drive an automobile); or why things look as they do.The basic assumption is that vision depends on the eye which is connected to the brain. The (...) author suggests that natural vision depends on the eyes in the head on a body supported by the ground, the brain being only the central organ of a complete visual system. When no constraints are put on the visual system, people look around, walk up to something interesting and move around it so as to see it from all sides, and go from one vista to another. That is natural vision—and what this book is about. (shrink)

Throughout, the book combines daring speculations with detailed investigations to portray the nature and status of rationality and the essential role that...

Each of the chapters in this volume devotes considerable attention to defining and elaborating the notion of the frame problem-one of the hard problems of artificial intelligence. Not only do the chapters clarify the problems at hand, they shed light on the different approaches taken by those in artificial intelligence and by certain philosophers who have been concerned with related problems in their field. The book should therefore not be read merely as a discussion of the frame problem narrowly conceived, (...) but also as a general analysis of what could be a major challenge to the design of computer systems exhibiting general intelligence. (shrink)

2014 Reprint of 1954 American Edition. Full facsimile of the original edition, not reproduced with Optical Recognition Software. This two volume classic comprises two titles: "Patterns of Plausible Inference" and "Induction and Analogy in Mathematics." This is a guide to the practical art of plausible reasoning, particularly in mathematics, but also in every field of human activity. Using mathematics as the example par excellence, Polya shows how even the most rigorous deductive discipline is heavily dependent on techniques of guessing, inductive (...) reasoning, and reasoning by analogy. In solving a problem, the answer must be guessed at before a proof can be given, and guesses are usually made from a knowledge of facts, experience, and hunches. The truly creative mathematician must be a good guesser first and a good prover afterward; many important theorems have been guessed but no proved until much later. In the same way, solutions to problems can be guessed, and a god guesser is much more likely to find a correct solution. This work might have been called "How to Become a Good Guesser."-From the Dust Jacket. (shrink)

Considers that intuitive predictions follow a judgmental heuristic-representativeness. By this heuristic, people predict the outcome that appears most representative of the evidence. Consequently, intuitive predictions are insensitive to the reliability of the evidence or to the prior probability of the outcome, in violation of the logic of statistical prediction. The hypothesis that people predict by representativeness was supported in a series of studies with both naive and sophisticated university students. The ranking of outcomes by likelihood coincided with the ranking by (...) representativeness, and Ss erroneously predicted rare events and extreme values if these happened to be representative. The experience of unjustified confidence in predictions and the prevalence of fallacious intuitions concerning statistical regression are traced to the representativeness heuristic. (shrink)

Hutchins examines a set of phenomena that have fallen between the established disciplines of psychology and anthropology, bringing to light a new set of relationships between culture and cognition.

Stanovich & West analyze individual differences with respect to response output (e.g., participants' numerical estimates). They do not analyze the underlying cognitive processes that led to the outputs; they thereby probably misclassify some non-normative responses as normative. Using base rate neglect and overconfidence as examples, I demonstrate the advantages of analyzing cognitive processes further.

This study of cognitive processes and scientific research begins with an autobiographical account of a research program that was designed to simulate scientific thinking. It explores such questions as: How do mental models, representations, expectations, and presumptions affect the creation of scientific knowledge? What is the effect of confirmation or disconfirmation on the process of experimentation and the direction of research? How does a scientist decide whether a model or theory is correct? The first-person narrative allows readers to follow the (...) research step by step and to work through the issues as the author grapples with them. The book also discusses important historical examples in which these issues have loomed large, among them the "great Devonian controversy," the etheric force controversy, and Kepler's theory of planetary motion. One fascinating chapter compares the cognitive styles of Bell and Edison and develops a cognitive framework that can be used to compare the creative processes of scientists and inventors. (shrink)

Recently, the theory theory has led to much interesting research. However, this is the first book to look at the theory in extensive detail and to systematically contrast it with other theories.

Can quite different values be rationally weighed against one another? Can the value of one thing always be ranked as greater than, equal to, or less than the value of something else? If the answer to these questions is no, then in what areas do we find commensurability and comparability unavailable? And what are the implications for moral and legal decision making? This book struggles with these questions, and arrives at distinctly different answers.".

[Correction Notice: An erratum for this article was reported in Vol 109 of Psychological Review. Due to circumstances that were beyond the control of the authors, the studies reported in "Models of Ecological Rationality: The Recognition Heuristic," by Daniel G. Goldstein and Gerd Gigerenzer overlap with studies reported in "The Recognition Heuristic: How Ignorance Makes Us Smart," by the same authors and with studies reported in "Inference From Ignorance: The Recognition Heuristic". In addition, Figure 3 in the Psychological Review article (...) was originally published in the book chapter and should have carried a note saying that it was used by permission of Oxford University Press.] One view of heuristics is that they are imperfect versions of optimal statistical procedures considered too complicated for ordinary minds to carry out. In contrast, the authors consider heuristics to be adaptive strategies that evolved in tandem with fundamental psychological mechanisms. The recognition heuristic, arguably the most frugal of all heuristics, makes inferences from patterns of missing knowledge. This heuristic exploits a fundamental adaptation of many organisms: the vast, sensitive, and reliable capacity for recognition. The authors specify the conditions under which the recognition heuristic is successful and when it leads to the counter-intuitive less-is-more effect in which less knowledge is better than more for making accurate inferences. (shrink)

The Empire of Chance tells how quantitative ideas of chance transformed the natural and social sciences, as well as daily life over the last three centuries. A continuous narrative connects the earliest application of probability and statistics in gambling and insurance to the most recent forays into law, medicine, polling and baseball. Separate chapters explore the theoretical and methodological impact in biology, physics and psychology. Themes recur - determinism, inference, causality, free will, evidence, the shifting meaning of probability - but (...) in dramatically different disciplinary and historical contexts. In contrast to the literature on the mathematical development of probability and statistics, this book centres on how these technical innovations remade our conceptions of nature, mind and society. Written by an interdisciplinary team of historians and philosophers, this readable, lucid account keeps technical material to an absolute minimum. It is aimed not only at specialists in the history and philosophy of science, but also at the general reader and scholars in other disciplines. (shrink)

Humans and animals make inferences about the world under limited time and knowledge. In contrast, many models of rational inference treat the mind as a Laplacean Demon, equipped with unlimited time, knowledge, and computational might. Following H. Simon's notion of satisficing, the authors have proposed a family of algorithms based on a simple psychological mechanism: one-reason decision making. These fast and frugal algorithms violate fundamental tenets of classical rationality: They neither look up nor integrate all information. By computer simulation, the (...) authors held a competition between the satisficing "Take The Best" algorithm and various "rational" inference procedures. The Take The Best algorithm matched or outperformed all competitors in inferential speed and accuracy. This result is an existence proof that cognitive mechanisms capable of successful performance in the real world do not need to satisfy the classical norms of rational inference. (shrink)

We tend to believe both that our current criteria of theory choice pick out the theories which we have most reason to believe are true, and that most of the theories which we believe to be true are likely to be someday shown false. It seems, then, that when theory choices are regarded in historical perspective, rationality pulls in two opposite directions, which I call "bounded" and "critical" rationality. The critical rationalist is the revolutionary scientist or the prescient lawgiver--someone whose (...) beliefs cannot be justified by his own criteria and so therefore restructures the criteria to make his belief justifiable. The ultimate beneficiary of this move is the bounded rationalist, someone who lives after the revolutionary and makes the latter's actions seem optimally rational by showing how they legitimate the worldview of the bounded rationalist. Bounded rationality, in this sense, occurs in Whiggish histories of science and judicial attempts at squaring particular decisions with the legal tradition. We consider both these cases in some detail, arguing that more than an ideological strategy, bounded rationality is a necessary response to the problem of being faced with a historical record which suggests that all the criteria of a good theory or a good law cannot be jointly maximized. (shrink)

In this book, I make use of an idea from economics to suggest how noble human tendencies might not only have survived the ruthless pressures of the material world, but actually have been nurtured by them.