Human Reasoning And Cognitive Science

A new proposal for integrating the employment of formal and empirical methods in the study of human reasoning. In Human Reasoning and Cognitive Science, Keith Stenning and Michiel van Lambalgen—a cognitive scientist and a logician—argue for the indispensability of modern mathematical logic to the study of human reasoning. Logic and cognition were once closely connected, they write, but were “divorced” in the past century; the psychology of deduction went from being central to the cognitive revolution to being the subject of widespread skepticism about whether human reasoning really happens outside the academy. Stenning and van Lambalgen argue that logic and reasoning have been separated because of a series of unwarranted assumptions about logic. Stenning and van Lambalgen contend that psychology cannot ignore processes of interpretation in which people, wittingly or unwittingly, frame problems for subsequent reasoning. The authors employ a neurally implementable defeasible logic for modeling part of this framing process, and show how it can be used to guide the design of experiments and interpret results.

This book brings together an influential sequence of papers that argue for a radical re-conceptualisation of the psychology of inference, and of cognitive science more generally. The papers demonstrate that the thesis that logic provides the basis of human inference is central to much cognitive science, although the commitment to this view is often implicit. They then note that almost all human inference is uncertain, whereas logic is the calculus of certain inference. This mismatch means that logic is not the appropriate model for human thought. Oaksford and Chater's argument draws on research in computer science, artificial intelligence and philosophy of science, in addition to experimental psychology. The authors propose that probability theory, the calculus of uncertain inference, provides a more appropriate model for human thought. They show how a probabilistic account can provide detailed explanations of experimental data on Wason's selection task, which many have viewed as providing a paradigmatic demonstration of human irrationality. Oaksford and Chater show that people's behaviour appears irrational only from a logical point of view, whereas it is entirely rational from a probabilistic perspective. The shift to a probabilistic framework for human inference has significant implications for the psychology of reasoning, cognitive science more generally, and forour picture of ourselves as rational agents.

For almost 2,500 years, the Western concept of what is to be human has been dominated by the idea that the mind is the seat of reason - humans are, almost by definition, the rational animal. In this text a more radical suggestion for explaining these puzzling aspects of human reasoning is put forward.

This book brings together an influential sequence of papers that argue for a radical re-conceptualisation of the psychology of inference, and of cognitive science more generally. The papers demonstrate that the thesis that logic provides the basis of human inference is central to much cognitive science, although the commitment to this view is often implicit. They then note that almost all human inference is uncertain, whereas logic is the calculus of certain inference. This mismatch means that logic is not the appropriate model for human thought. Oaksford and Chater's argument draws on research in computer science, artificial intelligence and philosophy of science, in addition to experimental psychology. The authors propose that probability theory, the calculus of uncertain inference, provides a more appropriate model for human thought. They show how a probabilistic account can provide detailed explanations of experimental data on Wason's selection task, which many have viewed as providing a paradigmatic demonstration of human irrationality. Oaksford and Chater show that people's behaviour appears irrational only from a logical point of view, whereas it is entirely rational from a probabilistic perspective. The shift to a probabilistic framework for human inference has significant implications for the psychology of reasoning, cognitive science more generally, and forour picture of ourselves as rational agents.

Advancing research in artificial intelligence is creating reasoning systems that increasingly emulate or surpass the power of human reasoning. This volume presents a critical analysis of current theory and research in psychological and computational sciences addressing reasoning processes. Distinguished from narrowly technical books on the one hand, and from general philosophical books on the other, this work gives a broad, structured, detailed, and critical account of advancing intellectual developments in theories on the nature of reasoning. Of special interest is the conclusion that artificial intelligence reasoning systems are deepening and broadening theories of human reasoning. A unified theory of intelligent reasoning encompassing natural and computational systems is an important current objective of cognitive science. Reasoning systems such as the CHARADE program, which simulates the course of inductive reasoning leading to medical discoveries, and the CONSYDERR program, which executes the robust theory of common sense reasoning, are important demonstrations of the feasibility of a unified theory of human and artificial intelligence.

As the eleventh volume in the New Directions in Cognitive Science series (formerly the Vancouver Studies in Cognitive Science series), this work promises superb scholarship and interdisciplinary appeal. It addresses three areas of current and varied interest: common sense, reasoning, and rationality. While common sense and rationality often have been viewed as two distinct features in a unified cognitive map, this volume offers novel, even paradoxical, views of the relationship. Comprised of outstanding essays from distinguished philosophers, it considers what constitutes human rationality, behavior, and intelligence covering diverse areas of philosophy, psychology, cognitive science, and computer science. Indeed, it is at the forefront of cognitive research and promises to be of unprecedented influence across numerous disciplines.

Are humans rational? Various experiments performed over the last several decades have been interpreted as showing that humans are irrational—we make significant and consistent errors in logical reasoning, probabilistic reasoning, similarity judgements, and risk-assessment, to name a few areas. But can these experiments establish human irrationality, or is it a conceptual truth that humans must be rational, as various philosophers have argued? In this book, Edward Stein offers a clear critical account of this debate about rationality in philosophy and cognitive science. He discusses concepts of rationality—the pictures of rationality that the debate centres on—and assesses the empirical evidence used to argue that humans are irrational. He concludes that the question of human rationality must be answered not conceptually but empirically, using the full resources of an advanced cognitive science. Furthermore, he extends this conclusion to argue that empirical considerations are also relevant to the theory of knowledge—in other words, that epistemology should be naturalized.

The advancement of knowledge concerning the complexities of human intellective processes can best be achieved by combining theory and research from the disciplines of cognitive psychology and artificial intelligence. Wagman explores various aspects of these disciplines to further his ideas. He examines the nature of the human intellect and proposes a theory of representation and intelligence that is applicable to human, computer, and animal cognition. He also evaluates theory and research concerned with structure and process in human reasoning and human problem solving. Several scientific discovery systems including BACON, FARENHEIT, and IDS are described in depth. The ability of these systems to emulate solutions to 10 types of scientific problems is examined. The capacity theory of language comprehension is also presented and extended to the domain of cognitive processes.