The thirty-five chapters in this book describe various judgmental heuristics and the biases they produce, not only in laboratory experiments but in important...

Ainslie argues that our responses to the threat of our own inconsistency determine the basic fabric of human culture. He suggests that individuals are more like populations of bargaining agents than like the hierarchical command structures envisaged by cognitive psychologists. The forces that create and constrain these populations help us understand so much that is puzzling in human action and interaction: from addictions and other self-defeating behaviors to the experience of willfulness, from pathological over-control and self-deception to subtler forms of (...) behavior such as altruism, sadism, gambling, and the 'social construction' of belief. This book integrates approaches from experimental psychology, philosophy of mind, microeconomics, and decision science to present one of the most profound and expert accounts of human irrationality available. It will be of great interest to philosophers and an important resource for professionals and students in psychology, economics and political science. (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)

Nissen and Bullemer's serial reaction time task has proven to be a useful model task for exploring implicit sequence learning. Neuropsychological research indicates that SRT learning may depend on the integrity of the basal ganglia, but not on medial temporal and diencephalic structures that are crucial for explicit learning. Recent neuroimaging research demonstrates that motor cortical areas , prefrontal, and parietal cortex also may be involved. This paper reviews this neuropsychological and neuroimaging research, but finds it lacking specific links between (...) structure and function. In order to promote better functional hypotheses, the second part of the paper examines the function of these brain areas from a broader perspective. Neuroimaging and neuropsychological research with human subjects, as well as neurophysiological and lesion research with animals, suggests a number component operations that these brain mechanisms may contribute to learning in the SRT task. (shrink)

Choice Outstanding Academic Title, 1996. In hundreds of articles by experts from around the world, and in overviews and "road maps" prepared by the editor, The Handbook of Brain Theory and Neural Networkscharts the immense progress made in recent years in many specific areas related to two great questions: How does the brain work? and How can we build intelligent machines? While many books have appeared on limited aspects of one subfield or another of brain theory and neural networks, the (...) Handbookcovers the entire sweep of topics—from detailed models of single neurons, analyses of a wide variety of biological neural networks, and connectionist studies of psychology and language, to mathematical analyses of a variety of abstract neural networks, and technological applications of adaptive, artificial neural networks. The excitement, and the frustration, of these topics is that they span such a broad range of disciplines including mathematics, statistical physics and chemistry, neurology and neurobiology, and computer science and electrical engineering as well as cognitive psychology, artificial intelligence, and philosophy. Thus, much effort has gone into making the Handbookaccessible to readers with varied backgrounds while still providing a clear view of much of the recent, specialized research in specific topics. The heart of the book, part III, comprises of 267 original articles by leaders in the various fields, arranged alphabetically by title. Parts I and II, written by the editor, are designed to help readers orient themselves to this vast range of material. Part I, Background, introduces several basic neural models, explains how the present study of brain theory and neural networks integrates brain theory, artificial intelligence, and cognitive psychology, and provides a tutorial on the concepts essential for understanding neural networks as dynamic, adaptive systems. Part II, Road Maps, provides entry into the many articles of part III through an introductory "Meta-Map" and twenty-three road maps, each of which tours all the Part III articles on the chosen theme. (shrink)

There is a simple view of motivation on which desires are like pain-killers; they come in different strengths, and their strength determines their efficacy. That is, the stronger a desire the greater its motivational force and, when two desires conflict, the stronger one “wins out” over the weaker. This view makes it puzzling how anyone could ever exhibit “strength of will” and act on the weaker desire, even when it is a desire for something more highly valued than what is (...) more strongly desired. When the will, as the agent of reason, enters the fray, an explanation of what a person is motivated enough to do must reckon not only with competing desires and their motivational forces, but also with the will’s capacity to be affected by different ones in ways not proportional to their force. However, this complication sheds little light, for if the will must bestow its stamp of approval on a desire before the desire leads to action, then, it would seem, motivational force should be measured by strength of effect on the will. And if that’s the way to measure motivational force, then, since by that measure one always acts on the desire that affects one’s will most, there is no problem of strength of will after all. But the problem seems real, however inapt the label. (shrink)