The way in which knowledge progresses, and especially our scientific knowledge, is by unjustified anticipations, by guesses, by tentative solutions to our problems, by conjectures. These conjectures are controlled by criticism: that is, by attempted refutations, which include severely critical tests. They may survive these tests; but they can never be positively justified: they can neither be established as certainly true nor even as 'probable'. Criticism of our conjectures is of decisive importance: by bringing out our mistakes it makes us (...) understand the difficulties of the problems which we try to solve. This is how we become better acquainted with our problem, and able to propose more mature solutions: the very refutation of a theory - that is, of a tentative solution to our problem - is always a step forward that takes us nearer the truth. And this is how we can learn from our mistakes. As we learn from our mistakes our knowledge grows, even though we may never know - that is, know for certain. Since our knowledge can grow, there can be no reason here for despair of reason. And since we can never know for certain, the can be no authority here for any claim to authority, for conceit over our knowledge, or for smugness. The essays and lectures of which this book is composed apply this thesis to many topics, ranging from problems of the philosophy and history of the physical and social sciences to historical and political problems. (shrink)

Isaac Levi is one of the preeminent philosophers in the areas of pragmatic rationality and epistemology. This collection of essays constitutes an important presentation of his original and influential ideas about rational choice and belief. A wide range of topics is covered, including consequentialism and sequential choice, consensus, voluntarism of belief, and the tolerance of the opinions of others. The essays elaborate on the idea that principles of rationality are norms that regulate the coherence of our beliefs and values with (...) our rational choices. The norms impose minimal constraints on deliberation and inquiry, but they also impose demands well beyond the capacities of deliberating agents. This major collection will be eagerly sought out by a wide range of philosophers in epistemology, logic, and philosophy of science, as well as economists, decision theorists, and statisticians. (shrink)

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Levi’s work in decision theory has for many years been a major influence on the field. His writings have raised important new issues and opened new lines of inquiry. This collection of his papers brings out the range of his recent studies and the close bearing of his work on the work of others.

This major work challenges some widely held positions in epistemology - those of Peirce and Popper on the one hand and those of Quine and Kuhn on the other.

Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial ...

The first full-scale history of cognitive science, this work addresses a central issue: What is the nature of knowledge?

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)

Actual AI research began auspiciously around 1955 with Allen Newell and Herbert Simon's work at the RAND Corporation. Newell and Simon proved that computers could do more than calculate. They demonstrated that computers were physical symbol systems whose symbols could be made to stand for anything, including features of the real world, and whose programs could be used as rules for relating these features. In this way computers could be used to simulate certain important aspects intelligence. Thus the information-processing model (...) of the mind was born. But, looking back over these fifty years, it seems that theoretical AI with its promise of a robot like HAL appears to be a perfect example of what Imre Lakatos has called a "degenerating research program". (shrink)

Computing Methodologies -- Artificial Intelligence.

"The best book available for non-mathematicians." — Contemporary Psychology. Superb nontechnical introduction to game theory and related disciplines, primarily as applied to the social sciences. Clear, comprehensive coverage of utility theory, 2-person zero-sum games, 2-person non-zero-sum games, n-person games, individual and group decision-making, much more. Appendixes. Bibliography. Graphs and figures.

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)

Decision making is usually viewed as involving a period of thought, while the decision maker assesses options, their likely consequences, and his or her preferences, and selects the preferred option. The process ends in a terminating action. In this view errors of thought will inevitably show up as errors of action; costs of thinking are to be balanced against costs of decision errors. Fast and frugal heuristics research has shown that, in some environments, modest thought can lead to excellent action. (...) In this paper we extend this work to situations in which action is taken after little or no thought. We show that these `highly active' or `decision cycles' processes can lead to excellent results at the cost of almost no thought. The paper examines the settings in which this effectiveness is possible, and lists a number of environmental features that are required for decision cycles to work well. Several research directions for analytical, laboratory, and field-based research are identified. (shrink)