Stephen Cole Kleene was one of the greatest logicians of the twentieth century and this book is the influential textbook he wrote to teach the subject to the next generation. It was first published in 1952, some twenty years after the publication of Godel's paper on the incompleteness of arithmetic, which marked, if not the beginning of modern logic. The 1930s was a time of creativity and ferment in the subject, when the notion of computable moved from the realm of (...) philosophical speculation to the realm of science. This was accomplished by the work of Kurt Gode1, Alan Turing, and Alonzo Church, who gave three apparently different precise definitions of computable. When they all turned out to be equivalent, there was a collective realization that this was indeed the right notion. Kleene played a key role in this process. One could say that he was there at the beginning of modern logic. He showed the equivalence of lambda calculus with Turing machines and with Godel's recursion equations, and developed the modern machinery of partial recursive functions. This textbook played an invaluable part in educating the logicians of the present. It played an important role in their own logical education.". (shrink)

Much research in the last two decades has demonstrated that human responses deviate from the performance deemed normative according to various models of decision making and rational judgment (e.g., the basic axioms of utility theory). This gap between the normative and the descriptive can be interpreted as indicating systematic irrationalities in human cognition. However, four alternative interpretations preserve the assumption that human behavior and cognition is largely rational. These posit that the gap is due to (1) performance errors, (2) computational (...) limitations, (3) the wrong norm being applied by the experimenter, and (4) a different construal of the task by the subject. In the debates about the viability of these alternative explanations, attention has been focused too narrowly on the modal response. In a series of experiments involving most of the classic tasks in the heuristics and biases literature, we have examined the implications of individual differences in performance for each of the four explanations of the normative/descriptive gap. Performance errors are a minor factor in the gap; computational limitations underlie non-normative responding on several tasks, particularly those that involve some type of cognitive decontextualization. Unexpected patterns of covariance can suggest when the wrong norm is being applied to a task or when an alternative construal of the task should be considered appropriate. Key Words: biases; descriptive models; heuristics; individual differences; normative models; rationality; reasoning. (shrink)

The mental model theory predicts variations in the percentage of errors in meta-propositional reasoning tasks but does not specify the nature of these errors. In the present study, we drew predictions concerning the nature of errors in a meta-propositional reasoning task by importing and elaborating the distinction between implicit and explicit models previously applied by the mental model theory to the domain of propositional reasoning. An experiment was conducted in which participants were asked to solve problems concerning the truth or (...) falsity of propositional assertions. The task was to determine the truth-status of two persons making a propositional assertion about their own truth-status and/or the truth-status of the other person. The results were consistent with the hypothesis that people may reason in ways that differ in the extent to which initially implicit models are made explicit. As such, the results corroborate a basic principle of the mental model theory: the errors that reasoners make are consistent with at least one of the mental models they construct during the process of reasoning. (shrink)

A Border Disputeintegrates the latest work in logic and semantics into a theory of language learning and presents six worked examples of how that theory revolutionizes cognitive psychology. Macnamara's thesis is set against the background of a fresh analysis of the psychologism debate of the 19th-century, which led to the current standoff between logic and psychology. The book presents psychologism through the writings of John Stuart Mill and Immanuel Kant, and its rejection by Gottlob Frege and Edmund Husserl. It then (...) works out the general thesis that logic ideally presents a competence theory for part of human reasoning and explains how logical intuition is grounded in properties of the mind. The next six chapters present examples that illustrate the relevance of logic to psychology. These problems are all in the semantics of child language (the learning of proper names, personal pronouns, sortals or common nouns, quantifiers, and the truth-functional connectives) and reflect Macnamara's rich background in developmental psychology, particularly child language - a field, he points out, that embraces all of cognition. Technical problems raised by but not included in the examples in the main part of the text are dealt with in a separate chapter. The book concludes by describing laws in cognitive psychology, or the type of science made possible by Macnamara's new theory. John Macnamara is Professor of Psychology and Director of the Program in the History and Philosophy of Science, McGill University. A Bradford Book. (shrink)

A formal theory of truth, alternative to tarski's 'orthodox' theory, based on truth-value gaps, is presented. the theory is proposed as a fairly plausible model for natural language and as one which allows rigorous definitions to be given for various intuitive concepts, such as those of 'grounded' and 'paradoxical' sentences.

The study of deductive reasoning has been a major paradigm in psychology for approximately the past 40 years. Research has shown that people make many logical errors on such tasks and are strongly influenced by problem content and context. It is argued that this paradigm was developed in a context of logicist thinking that is now outmoded. Few reasoning researchers still believe that logic is an appropriate normative system for most human reasoning, let alone a model for describing the process (...) of human reasoning, and many use the paradigm principally to study pragmatic and probabilistic processes. It is suggested that the methods used for studying reasoning be reviewed, especially the instructional context, which necessarily defines pragmatic influences as biases. (shrink)

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

Chomsky proposes a reformulation of the theory of transformational generative grammar that takes recent developments in the descriptive analysis of particular ...

Deductive reasoning shares with other forms of thinking a reliance on strategies, as shown by the results of three experiments on the nature and development of control strategies to solve suppositional deductions. These puzzles are based on assertors who may or may not be telling the truth, and their assertions about their status as truthtellers and liars. The first experiment shows that reasoners make backward inferences as well as forward inferences, to short-cut their way through the alternatives, and the generation (...) of suppositions is a source of difficulty. The second experiment establishes that the elimination of the suppositional status of an individual does not render problems easier. The third experiment shows that reasoners can improve their reasoning accuracy and speed spontaneously, without feedback, and it clarifies the transfer of strategies and their development. We discuss the implications of these data for alternative theories of suppositional deduction and for the relationship between reasoning and other forms of thinking such as problem solving. (shrink)

Two experiments investigated inferences based on suppositions. In Experiment 1, the subjects decided whether suppositions about individuals' veracity were consistent with their assertions—for example, whether the supposition “Ann is telling the truth and Beth is telling a lie”, is consistent with the premises: “Ann asserts: I am telling the truth and Beth is telling the truth. Beth asserts: Ann is telling the truth”. It showed that these inferences are more difficult than ones based on factual premises: “Ann asserts: I live (...) in Dublin and Beth lives in Dublin”. There was no difference between problems about truthtellers and liars, who always told the truth or always lied, and normals, who sometimes told the truth and sometimes lied. In Experiment 2, the subjects made inferences about factual matters set in three contexts: a truth-inducing context in which friends confided their personality characteristics, a lie-inducing context in which business rivals advertised their products, and a neutral context in which computers printed their program characteristics. Given the supposition that the individuals were lying, it was more difficult to make inferences in a truth-inducing context than in the other two contexts. We discuss the implications of our results for everyday reasoning from suppositions, and for theories of reasoning based on models or inference rules. (shrink)

A provocative assessment of human thought and behavior, reissued with a new afterword, explores a range of conundrums from the ability of the mind to perceive three dimensions to the nature of consciousness, in an account that draws on ...

"Semantic Truth Theories" uses the techniques of mathematical logic to develop a new semantic treatment of the concept of truth based on ideas of Saul Kripke. Yael Cohen goes on to solve the Liar paradox, Hempel's raven paradox in the philosophy of science, and other classical problems of philosophy. She does this by enlarging the scope of formal logic to include concepts of presupposition besides the usual implication. The book thus provides a unified treatment of many topics having to do (...) with truth, topics whose deep and unsuspected interconnections are not visible without the insights of mathematical knowledge which the author elaborates. The early chapters of the book contain an accessible introduction to semantic paradoxes which should be useful to students. (shrink)

What is the mind? How does it work? How does it influence behavior? Some psychologists hope to answer such questions in terms of concepts drawn from computer science and artificial intelligence. They test their theories by modeling mental processes in computers. This book shows how computer models are used to study many psychological phenomena--including vision, language, reasoning, and learning. It also shows that computer modeling involves differing theoretical approaches. Computational psychologists disagree about some basic questions. For instance, should the mind (...) be modeled by digital computers, or by parallel-processing systems more like brains? Do computer programs consist of meaningless patterns, or do they embody (and explain) genuine meaning? (shrink)

Bringing together powerful new tools from set theory and the philosophy of language, this book proposes a solution to one of the few unresolved paradoxes from antiquity, the Paradox of the Liar. Treating truth as a property of propositions, not sentences, the authors model two distinct conceptions of propositions: one based on the standard notion used by Bertrand Russell, among others, and the other based on J.L. Austin's work on truth. Comparing these two accounts, the authors show that while the (...) Russellian conception of the relation between sentences, propositions, and truth is crucially flawed in limiting cases, the Austinian perspective has fruitful applications to the analysis of semantic paradox. In the course of their study of a language admitting circular reference and containing its own truth predicate, Barwise and Etchemendy also develop a wide range of model-theoretic techniques--based on a new set-theoretic tool, Peter Aczel's theory of hypersets--that open up new avenues in logical and formal semantics. (shrink)