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.

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 behavior 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 for our picture of ourselves as rational agents.

Are people rational? This question was central to Greek thought; and has been at the heart of psychology, philosophy, rational choice in social sciences, and probabilistic approaches to artificial intelligence. This book provides a radical re-appraisal of conventional wisdom in the psychology of reasoning.
For almost two and a half thousand years, the Western conception of what it is to be a human being has been dominated by the idea that the mind is the seat of reason - humans are, almost by definition, the rational animal. From Aristotle to the present day, rationality has been explained by comparison to systems of logic, which distinguish valid (i.e., rationally justified) from invalid arguments. Within psychology and cognitive science, such a logicist conception of the mind was adopted wholeheartedly from Piaget onwards. Simultaneous with the construction of the logicist program in cognition, other researchers found that people appeared surprisingly and systematically illogical in some experiments. Proposals within the logicist paradigm suggested that these were mere performance errors, although in some reasoning tasks only as few as 5% of people's reasoning was logically correct.
In this book a more radical suggestion for explaining these puzzling aspects of human reasoning is put forward: the Western conception of the mind as a logical system is flawed at the very outset. The human mind is primarily concerned with practical action in the face of a profoundly complex and uncertain world. Oaksford and Chater argue that cognition should be understood in terms of probability theory, the calculus of uncertain reasoning, rather than in terms of logic, the calculus of certainreasoning. Thus, the logical mind should be replaced by the probabilistic mind - people may possess not logical rationality, but Bayesian rationality.

The rational analysis method, first proposed by John R. Anderson, has been enormously influential in helping us understand high-level cognitive processes.
The Probabilistic Mind is a follow-up to the influential and highly cited 'Rational Models of Cognition' (OUP, 1998). It brings together developments in understanding how, and how far, high-level cognitive processes can be understood in rational terms, and particularly using probabilistic Bayesian methods. It synthesizes and evaluates the progress in the past decade, taking into account developments in Bayesian statistics, statistical analysis of the cognitive 'environment' and a variety of theoretical and experimental lines of research. The scope of the book is broad, covering important recent work in reasoning, decision making, categorization, and memory. Including chapters from many of the leading figures in this field,
The Probabilistic Mind will be valuable for psychologists and philosophers interested in cognition.