In his new foreword to this edition, Hilary Putnam forcefully rejects these nativist claims.

This classic work in the philosophy of physical science is an incisive and readable account of the scientific method. Pierre Duhem was one of the great figures in French science, a devoted teacher, and a distinguished scholar of the history and philosophy of science. This book represents his most mature thought on a wide range of topics.

Professor Brown describes and criticises the major classical model of rationality and offers a new model of this central concept in the history of philosophy and of science.

This article described three heuristics that are employed in making judgements under uncertainty: representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value (...) is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty. (shrink)

This book represents the first major attempt by any author to provide an integrated account of the evidence for bias in human reasoning across a wide range of disparate psychological literatures. The topics discussed involve both deductive and inductive reasoning as well as statistical judgement and inference. In addition, the author proposes a general theoretical approach to the explanations of bias and considers the practical implications for real world decision making. The theoretical stance of the book is based on a (...) distinction between preconscious heuristic processes which determine the mental representation of 'relevant' features of the problem content, and subsequent analytic reasoning processes which generate inferences and judgements. Phenomena discussed and interpreted within this framework include feature matching biases in propositional reasoning, confirmation bias, biasing and debiasing effects of knowledge on reasoning, and biases in statistical judgement normally attributed to 'availability' and 'representativeness' heuristics. In the final chapter, the practical consequences of bias for real life decision making are considered, together with various issues concerning the problem of 'debiasing'. The major approaches discussed are those involving education and training on the one hand, and the development of intelligent software and interactive decision aids on the other. (shrink)

Davidson attacks the intelligibility of conceptual relativism, i.e. of truth relative to a conceptual scheme. He defines the notion of a conceptual scheme as something ordering, organizing, and rendering intelligible empirical content, and calls the position that employs both notions scheme-content dualism. He argues that such dualism is untenable since: not only can we not parcel out empirical content sentence per sentence but also the notion of uninterpreted content to which several schemes are relative, and the related notion of a (...) theory ”fitting the evidence’, can be shown to lack intelligibility too. Davidson argues further that belief in incommensurable schemes or non-intertranslatable languages is possible only on violating a correct understanding of interpretability : if we succeed in interpreting someone else then we have shown there is no need to speak of two conceptual schemes, while if we fail ”there is no ground for speaking of two.’. (shrink)

The object of this paper is to show why recent research in the psychology of deductive and probabilistic reasoning does not have.

This is a unique book. It is excellently written, crammed with information, wise and a pleasure to read.' ---Daniel C. Dennett, Tufts University.

We propose that people typically reason about realistic situations using neither content-free syntactic inference rules nor representations of specific experiences. Rather, people reason using knowledge structures that we term pragmatic reasoning schemas, which are generalized sets of rules defined in relation to classes of goals. Three experiments examined the impact of a “permission schema” on deductive reasoning. Experiment 1 demonstrated that by evoking the permission schema it is possible to facilitate performance in Wason's selection paradigm for subjects who have had (...) no experience with the specific content of the problems. Experiment 2 showed that a selection problem worded in terms of an abstract permission elicited better performance than one worded in terms of a concrete but arbitrary situation, providing evidence for an abstract permission schema that is free of domain-specific content. Experiment 3 provided evidence that evocation of a permission schema affects not only tasks requiring procedural knowledge, but also a linguistic rephrasing task requiring declarative knowledge. In particular, statements in the form if p then q were rephrased into the form p only if q with greater frequency for permission than for arbitrary statements, and rephrasings of permission statements produced a pattern of introduction of modals totally unlike that observed for arbitrary conditional statements. Other pragmatic schemas, such as “causal” and “evidence” schemas can account for both linguistic and reasoning phenomena that alternative hypotheses fail to explain. (shrink)

This volume tackles the slippery subject of 'meaning'.

The mathematical theory of communication.

The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.

Scientific reasoning is—and ought to be—conducted in accordance with the axioms of probability. This Bayesian view—so called because of the central role it accords to a theorem first proved by Thomas Bayes in the late eighteenth ...

'Is there any other point to which you would wish to draw my attention?' 'To the curious incident of the dog in the night-time.' 'The dog did nothing in the night-time.' 'That was the curious incident, ' remarked Sherlock Holmes. The quotation from A. Conan Doyle with which this book begins, is a delightfully appropriate summation of the authors' point of view garnered from their fifteen years of experiments on the psychology of reasoning. Dr. Wason and Dr. Johnson-Laird are intrigued (...) by the extent to which most individuals can be considered naturally rational thinkers. They present here the surprising results of their comprehensive investigations of how humans draw explicit conclusions from evidence. Given a set of assertions, the authors write, to what extent can the individual appreciate all that follows from them by virtue of logic alone, and remain unseduced by plausible, but fallacious conclusions? We are not concerned with whether these assertions are true or false, nor with whether the individual holds them among his beliefs, nor with whether they are sane or silly. At the core of the Psychology of Reasoning is a vigorous discussion that incorporates various illustrations--some of them humorous, all of them fascinating--of the use of reason under a wide variety of different conditions. Particular emphasis is placed on the difficulties involved in dealing with negatively marked information that must be combined and used with other information for reaching conclusions. Thorough treatment is given as well to the search for plausible contexts that will render anomalous or ambiguous statements sensible. The authors have strived to isolate the components ofinference, the basic steps of any kind of deductive activity, in order to determine the psychological processes involved in them. What has been the outcome of this research? Dr. Wason and Dr. Johnson-Laird conclude, our research has suggested that the individual's logical competence may be either enhanced or limited by performance variables. And, of these, content has turned out to be vitally important for revealing, or obscuring structure. At best, we can all think like logicians; at worst, logicians all think like us. (shrink)

A scientific community cannot practice its trade without some set of received beliefs. These beliefs form the foundation of the "educational initiation that prepares and licenses the student for professional practice". The nature of the "rigorous and rigid" preparation helps ensure that the received beliefs are firmly fixed in the student's mind. Scientists take great pains to defend the assumption that scientists know what the world is like...To this end, "normal science" will often suppress novelties which undermine its foundations. Research (...) is therefore not about discovering the unknown, but rather "a strenuous and devoted attempt to force nature into the conceptual boxes supplied by professional education". (shrink)

Thomas S. Kuhn's classic book is now available with a new index.

From Descartes to Popper, philosophers have criticized and tried to improve the strategies of reasoning invoked in science and in everyday life. In recent years leading cognitive psychologists have painted a detailed, controversial, and highly critical portrait of common sense reasoning. Stephen Stich begins with a spirited defense of this work and a critique of those writers who argue that widespread irrationality is a biological or conceptual impossibility.Stich then explores the nature of rationality and irrationality: What is it that distinguishes (...) good reasoning from bad? He rejects the most widely accepted approaches to this question approaches which unpack rationality by appeal to truth, to reflective equilibrium or conceptual analysis. The alternative he defends grows out of the pragmatic tradition in which reasoning is viewed as a cognitive tool. Stich's version of pragmatism leads to a radical epistemic relativism and he argues that the widespread abhorrence of relativism is ill founded. (shrink)

1. When we attribute beliefs, desires, and other states of common sense psychology to a person, or for that matter to an animal or an artifact, we are assuming or presupposing that the person or object can be treated as an intentional system. 2. An intentional system is one which is rational through and through; its beliefs are those it ought to have, given its perceptual capacities, its epistemic needs, and its biography…. Its desires are those it ought to have, (...) given its biological needs and the most practicable means of satisfying them…. And its behavior will consist of those acts that it would be rational for an agent with those beliefs and desires to perform. [beliefs + desires  action] 3. If rationality is absent, we cannot coherently ascribe beliefs at all. 4. Therefore, no experiment could demonstrate that people systematically invoke invalid or irrational inferential strategies. (shrink)

I examine the phenomenon of implicit learning, the process by which knowledge about the rule-governed complexities of the stimulus environment is acquired independently of conscious attempts to do so. Our research with the two seemingly disparate experimental paradigms of synthetic grammar learning and probability learning, is reviewed and integrated with other approaches to the general problem of unconscious cognition. The conclusions reached are as follows: Implicit learning produces a tacit knowledge base that is abstract and representative of the structure of (...) the environment; such knowledge is optimally acquired independently of conscious efforts to learn; and it can be used implicitly to solve problems and make accurate decisions about novel stimulus circumstances. Various epistemological issues and related problems such as intuition, neuroclinical disorders of learning and memory, and the relationship of evolutionary processes to cognitive science are also discussed. (shrink)

Classical symbolic computational models of cognition are at variance with the empirical findings in the cognitive psychology of memory and inference. Standard symbolic computers are well suited to remembering arbitrary lists of symbols and performing logical inferences. In contrast, human performance on such tasks is extremely limited. Standard models donot easily capture content addressable memory or context sensitive defeasible inference, which are natural and effortless for people. We argue that Connectionism provides a more natural framework in which to model this (...) behaviour. In addition to capturing the gross human performance profile, Connectionist systems seem well suited to accounting for the systematic patterns of errors observed in the human data. We take these arguments to counter Fodor and Pylyshyn's (1988) recent claim that Connectionism is, in principle, irrelevant to psychology. (shrink)