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Classic work by one of the most brilliant figures in post-war analytic philosophy.
Conditionals, Paradox, and Probability comprises fifteen original essays on themes from the work of Dorothy Edgington, the first woman to hold a chair in philosophy at Oxford. Eminent contributors from philosophy and linguistics discuss a range of topics including conditionals, vagueness, knowledge, reasoning, and probability.
An enduring question in the philosophy of science is the question of whether a scientific theory deserves more credit for its successful predictions than it does for accommodating data that was already known when the theory was developed. In The Paradox of Predictivism, Eric Barnes argues that the successful prediction of evidence testifies to the general credibility of the predictor in a way that evidence does not when the evidence is used in the process of endorsing the theory. He illustrates his argument with an important episode from nineteenth-century chemistry, Mendeleev's Periodic Law and its successful predictions of the existence of various elements. The consequences of this account of predictivism for the realist/anti-realist debate are considerable, and strengthen the status of the 'no miracle' argument for scientific realism. Barnes's important and original contribution to the debate will interest a wide range of readers in philosophy of science.
The modern discussion on the concept of truthlikeness was started in 1960. In his influential Word and Object, W. V. O. Quine argued that Charles Peirce's definition of truth as the limit of inquiry is faulty for the reason that the notion 'nearer than' is only "defined for numbers and not for theories". In his contribution to the 1960 International Congress for Logic, Methodology, and Philosophy of Science at Stan ford, Karl Popper defended the opposite view by defining a compara tive notion of verisimilitude for theories. was originally introduced by the The concept of verisimilitude Ancient sceptics to moderate their radical thesis of the inaccessibility of truth. But soon verisimilitudo, indicating likeness to the truth, was confused with probabilitas, which expresses an opiniotative attitude weaker than full certainty. The idea of truthlikeness fell in disrepute also as a result of the careless, often confused and metaphysically loaded way in which many philosophers used - and still use - such concepts as 'degree of truth', 'approximate truth', 'partial truth', and 'approach to the truth'. Popper's great achievement was his insight that the criticism against truthlikeness - by those who urge that it is meaningless to speak about 'closeness to truth' - is more based on prejudice than argument.
An introduction to awe-inspiring ideas at the brink of paradox: infinities of different sizes, time travel, probability and measure theory, and computability theory. This book introduces the reader to awe-inspiring issues at the intersection of philosophy and mathematics. It explores ideas at the brink of paradox: infinities of different sizes, time travel, probability and measure theory, computability theory, the Grandfather Paradox, Newcomb's Problem, the Principle of Countable Additivity. The goal is to present some exceptionally beautiful ideas in enough detail to enable readers to understand the ideas themselves (rather than watered-down approximations), but without supplying so much detail that they abandon the effort. The philosophical content requires a mind attuned to subtlety; the most demanding of the mathematical ideas require familiarity with college-level mathematics or mathematical proof. The book covers Cantor's revolutionary thinking about infinity, which leads to the result that some infinities are bigger than others; time travel and free will, decision theory, probability, and the Banach-Tarski Theorem, which states that it is possible to decompose a ball into a finite number of pieces and reassemble the pieces so as to get two balls that are each the same size as the original. Its investigation of computability theory leads to a proof of Gödel's Incompleteness Theorem, which yields the amazing result that arithmetic is so complex that no computer could be programmed to output every arithmetical truth and no falsehood. Each chapter is followed by an appendix with answers to exercises. A list of recommended reading points readers to more advanced discussions. The book is based on a popular course (and MOOC) taught by the author at MIT.
In this rigorous investigation into the logic of truth Anil Gupta and Nuel Belnap explain how the concept of truth works in both ordinary and pathological contexts. The latter include, for instance, contexts that generate Liar Paradox. Their central claim is that truth is a circular concept. In support of this claim they provide a widely applicable theory (the "revision theory") of circular concepts. Under the revision theory, when truth is seen as circular both its ordinary features and its pathological features fall into a simple understandable pattern. The Revision Theory of Truth is unique in placing truth in the context of a general theory of definitions. This theory makes sense of arbitrary systems of mutually interdependent concepts, of which circular concepts, such as truth, are but a special case.
This volume brings together many of Terence Horgan's essays on paradoxes: Newcomb's problem, the Monty Hall problem, the two-envelope paradox, the sorites paradox, and the Sleeping Beauty problem. Newcomb's problem arises because the ordinary concept of practical rationality constitutively includes normative standards that can sometimes come into direct conflict with one another. The Monty Hall problem reveals that sometimes the higher-order fact of one's having reliably received pertinent new first-order information constitutes stronger pertinent new information than does the new first-order information itself. The two-envelope paradox reveals that epistemic-probability contexts are weakly hyper-intensional; that therefore, non-zero epistemic probabilities sometimes accrue to epistemic possibilities that are not metaphysical possibilities; that therefore, the available acts in a given decision problem sometimes can simultaneously possess several different kinds of non-standard expected utility that rank the acts incompatibly. The sorites paradox reveals that a certain kind of logical incoherence is inherent to vagueness, and that therefore, ontological vagueness is impossible. The Sleeping Beauty problem reveals that some questions of probability are properly answered using a generalized variant of standard conditionalization that is applicable to essentially indexical self-locational possibilities, and deploys "preliminary" probabilities of such possibilities that are not prior probabilities. The volume also includes three new essays: one on Newcomb's problem, one on the Sleeping Beauty problem, and an essay on epistemic probability that articulates and motivates a number of novel claims about epistemic probability that Horgan has come to espouse in the course of his writings on paradoxes. A common theme unifying these essays is that philosophically interesting paradoxes typically resist either easy solutions or solutions that are formally/mathematically highly technical. Another unifying theme is that such paradoxes often have deep-sometimes disturbing-philosophical morals.
Priest advocates and defends the view that there are true contradictions (dialetheism), a perspective that flies in the face of orthodoxy in Western philosophy since Aristole and remains at the centre of philosophical debate. This edition contains the author's reflections on developments since 1987.
Tracking Truth presents a unified treatment of knowledge, evidence, and epistemological realism and anti-realism about scientific theories. A wide range of knowledge-related phenomena, especially but not only in science, strongly favour the idea of tracking as the key to what makes something knowledge. A subject who tracks the truth - an idea first formulated by Robert Nozick - has the ability to follow the truth through time and changing circumstances. Epistemologistsrightly concluded that Nozick's theory was not viable, but a simple revision of that view is not only viable but superior to other current views. In this new tracking account of knowledge, in contrast to the old view, knowledge has the property of closure under known implication, and troublesome counterfactualsare replaced with well-defined conditional probability statements. Of particular interest are the new view's treatment of skepticism, reflective knowledge, lottery propositions, knowledge of logical truth, and the question why knowledge is power in the Baconian sense.Ideally, evidence indicates a hypothesis and discriminates it from other possible hypotheses. This is the idea behind a tracking view of evidence, and Sherrilyn Roush provides a defence of a confirmation theory based on the Likelihood Ratio. The accounts of knowledge and evidence she offers provide a deep and seamless explanation of why having better evidence makes one more likely to have knowledge. Roush approaches the question of epistemological realism about scientific theories through thequestion what is required for evidence, and rejects both traditional realist and traditional anti-realist positions in favour of a new position which evaluates realist claims in a piecemeal fashion according to a general standard of evidence. The results show that while anti-realists were immodest indeclaring a priori what science could not do, realists were excessively sanguine about how far our actual evidence has so far taken us.
Anyone involved in the philosophy of science is naturally drawn into the study of the foundations of probability. Different interpretations of probability, based on competing philosophical ideas, lead to different statistical techniques, and frequently to mutually contradictory consequences.This unique book presents a new interpretation of probability, rooted in the traditional interpretation that was current in the 17th and 18th centuries. Mathematical models are constructed based on this interpretation, and statistical inference and decision theory are applied, including some examples in artificial intelligence, solving the main foundational problems. Nonstandard analysis is extensively developed for the construction of the models and in some of the proofs. Many nonstandard theorems are proved, some of them new, in particular, a representation theorem that asserts that any stochastic process can be approximated by a process defined over a space with equiprobable outcomes.