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Probabilistic knowledge /
Sarah Moss argues that in addition to full beliefs, credences can constitute knowledge. She introduces the notion of probabilistic content and shows how it plays a central role not only in epistemology, but in the philosophy of mind and language. Just you can believe and assert propositions, you can...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Oxford :
Oxford University Press,
2018.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 001 | EBSCO_on1022945279 | ||
| 003 | OCoLC | ||
| 005 | 20231017213018.0 | ||
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| 100 | 1 | |a Moss, Sarah, |e author. | |
| 245 | 1 | 0 | |a Probabilistic knowledge / |c Sarah Moss. |
| 264 | 1 | |a Oxford : |b Oxford University Press, |c 2018. | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Online resource; title from PDF title page (EBSCO, viewed February 19, 2018). | |
| 505 | 0 | |a Cover; Probabilistic Knowledge; Copyright; Dedication; Contents; Preface; 1: The case for probabilistic contents; 1.1 Probabilistic beliefs; 1.2 An argument for probabilistic contents of belief; 1.3 The roles played by contents of belief; 1.4 Full beliefs; 1.5 Alternative roles for contents of belief; 2: The case for probabilistic assertion; 2.1 Familiar arguments against propositional contents of assertion; 2.2 Foundational arguments for probabilistic contents of assertion; 2.3 Modeling communication; 2.4 Epistemic modals and indicative conditionals. | |
| 505 | 8 | |a 2.5 A test battery for probabilistic content3: Epistemic modals and probability operators; 3.1 Motivations for my semantics; 3.2 Embedded epistemic vocabulary; 3.3 Challenges for other theories; 3.4 A semantics for epistemic modals and probability operators; 3.5 A semantics for simple sentences; 3.6 The relationship between credence and full belief; 4: Indicative conditionals; 4.1 Probabilities of conditionals as conditional probabilities; 4.2 A semantics for conditionals; 4.3 Why probabilities of conditionals are not conditional probabilities; 4.4 A semantics for other logical operators. | |
| 505 | 8 | |a 4.5 The pragmatics of epistemic vocabulary5: The case for probabilistic knowledge; 5.1 The thesis that probabilistic beliefs can be knowledge; 5.2 Testimony; 5.3 Perception; 5.4 Arguments for probabilistic contents of experience; 5.5 Other sources of knowledge; 5.6 Justified true belief without knowledge; 5.7 Traditional theories of knowledge; 5.8 An alternative mental state?; 5.9 Applications; 6: Factivity; 6.1 Alternatives to probabilistic knowledge?; 6.2 The contents of knowledge ascriptions; 6.3 Frequently asked questions; 6.4 Relativism; 6.5 Objective chance; 7: Skepticism. | |
| 505 | 8 | |a 7.1 A skeptical puzzle7.2 The argument from inconsistency; 7.3 The argument from closure; 7.4 The argument from disjunction; 7.5 The argument from safety; 8: Knowledge and belief; 8.1 The knowledge norm of belief; 8.2 Peer disagreement; 8.3 Applying the knowledge norm of belief; 8.4 Statistical inference; 8.5 Responses to skepticism about perceptual knowledge; 9: Knowledge and action; 9.1 Knowledge norms of action; 9.2 Addressing objections; 9.3 Applying knowledge norms of action; 9.4 Pragmatic encroachment; 9.5 Transformative experience; 10: Knowledge and persons; 10.1 Statistical evidence. | |
| 505 | 8 | |a 10.2 An account of legal proof10.3 Applying knowledge standards of proof; 10.4 Racial and other profiling; 10.5 Applying the rule of consideration; Appendix: A formal semantics for epistemic vocabulary; A.1 Background; A.2 Epistemic modals and probability operators; A.3 Simple sentences; A.4 Indicative conditionals; A.5 Other logical operators; References; Index. | |
| 520 | |a Sarah Moss argues that in addition to full beliefs, credences can constitute knowledge. She introduces the notion of probabilistic content and shows how it plays a central role not only in epistemology, but in the philosophy of mind and language. Just you can believe and assert propositions, you can believe and assert probabilistic contents. | ||
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 650 | 0 | |a Probabilities. | |
| 650 | 0 | |a Logic, Symbolic and mathematical. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 2 | |a Probability | |
| 650 | 2 | |a Artificial Intelligence | |
| 650 | 6 | |a Probabilités. | |
| 650 | 6 | |a Logique symbolique et mathématique. | |
| 650 | 6 | |a Intelligence artificielle. | |
| 650 | 7 | |a probability. |2 aat | |
| 650 | 7 | |a artificial intelligence. |2 aat | |
| 650 | 7 | |a MATHEMATICS |x Applied. |2 bisacsh | |
| 650 | 7 | |a MATHEMATICS |x Probability & Statistics |x General. |2 bisacsh | |
| 650 | 7 | |a Artificial intelligence |2 fast | |
| 650 | 7 | |a Logic, Symbolic and mathematical |2 fast | |
| 650 | 7 | |a Probabilities |2 fast | |
| 776 | 0 | 8 | |i Print version : |z 9780198792154 |
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