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The author or concept searched is found in the following 29 entries.
| Disputed term/author/ism | Author |
Entry |
Reference |
|---|---|---|---|
| Change | AI Research | Norvig I 566 Change/probability/time/inference/AI research/Norvig/Russell: Agents in partially observable environments must be able to keep track of the current state, to the extent that their sensors allow. (…) an agent maintains a belief state that represents which states of the world are currently possible. >Belief states/Norvig. From the belief state and a transition model, the agent can predict how the world might evolve in the next time step. From the percepts observed and a sensor model, the agent can update the belief state. [There are two ways of representing belief states] (…) a) by explicitly enumerated sets of states, b) by logical formulas. Those approaches defined belief states in terms of which world states were possible, but could say nothing about which states were likely or unlikely. Problem: a changing world is modeled using a variable for each aspect of the world state at each point in time. The transition and sensor models may be uncertain: the transition model describes the probability distribution of the variables at time t, given the state of the world at past times, while the sensor model describes the probability of each percept at time t, given the current state of the world. Solution: three specific kinds of models: hidden Markov models, Kalman filters, and dynamic Bayesian networks (which include hidden Markov models and Kalman filters as special cases). Norvig I 567 To assess the current state from the history of evidence and to predict the outcomes of treatment actions, we must model these changes. We view the world as a series of snapshots, or time slices, each of which contains a set of random variables, some observable and some not. ((s) Cf. >Four dimensionalism/Philosophical theories). Norvig I 568 (…) the next step is to specify how the world evolves (the transition model) and how the evidence variables get their values (the sensor model). Norvig I 570 Order: increasing the order can always be reformulated as an increase in the set of state variables, keeping the order fixed. Notice that adding state variables might improve the system’s predictive power but also increases the prediction requirements (…). Norvig I 603 Problem: data association: When trying to keep track of many objects, uncertainty arises as to which observations belong to which objects—the data association problem. The number of association hypotheses is typically intractably large, but MCMC and particle filtering algorithms for data association work well in practice. Norvig I 602 MCMC: An MCMC algorithm explores the space of assignment histories. Norvig I 603 Change: The changing state of the world is handled by using a set of random variables to represent the state at each point in time. Representations: can be designed to satisfy the Markov property, so that the future is independent of the past given the present. Combined with the assumption that the process is stationary—that is, the dynamics do not change over time—this greatly simplifies the representation. Probability: A temporal probability model can be thought of as containing a transition model describing the state evolution and a sensor model describing the observation process. >Inference/AI research. Historical development: Many of the basic ideas for estimating the state of dynamical systems came from the mathematician C. F. Gauss (1809)(1), who formulated a deterministic least-squares algorithm for the problem of estimating orbits from astronomical observations. A. A. Markov (1913)(2) developed what was later called the Markov assumption in his analysis of stochastic processes; Norvig I 604 (…). The general theory of Markov chains and their mixing times is covered by Levin et al. (2008)(3). Significant classified work on filtering was done during World War II by Wiener (1942)(4) for continuous-time processes and by Kolmogorov (1941)(5) for discrete-time processes. Although this work led to important technological developments over the next 20 years, its use of a frequency-domain representation made many calculations quite cumbersome. Direct state-space modeling of the stochastic process turned out to be simpler, as shown by Peter Swerling (1959)(6) and Rudolf Kalman (1960)(7). The hidden Markov model and associated algorithms for inference and learning, including the forward–backward algorithm, were developed by Baum and Petrie (1966)(8). The Viterbi algorithm first appeared in (Viterbi, 1967)(9). Similar ideas also appeared independently in the Kalman filtering community (Rauch et al., 1965)(10). The forward–backward algorithm was one of the main precursors of the general formulation of the EM algorithm (Dempster et al., 1977)(11) (…). Dynamic Bayesian networks (DBNs) can be viewed as a sparse encoding of a Markov process and were first used in AI by Dean and Kanazawa (1989b)(12), Nicholson and Brady (1992)(13), and Kjaerulff (1992)(14). The last work extends the HUGIN Bayes net system to accommodate dynamic Bayesian networks. The book by Dean and Wellman (1991)(15) helped popularize DBNs and the probabilistic approach to planning and control within AI. Murphy (2002)(16) provides a thorough analysis of DBNs. Dynamic Bayesian networks have become popular for modeling a variety of complex motion processes in computer vision (Huang et al., 1994(17); Intille and Bobick, 1999)(18). Like HMMs, they have found applications in speech recognition (Zweig and Russell, 1998(19)); Richardson et al., 2000(20); Stephenson et al., 2000(21); Nefian et al., 2002(22); Livescu et al., 2003(23)), Norvig I 605 genomics (Murphy and Mian, 1999(24); Perrin et al., 2003(25); Husmeier, 2003(26)) and robot localization (Theocharous et al., 2004)(27). The link between HMMs and DBNs, and between the forward–backward algorithm and Bayesian network propagation, was made explicitly by Smyth et al. (1997)(28). A further unification with Kalman filters (and other statistical models) appears in Roweis and Ghahramani (1999)(29). Procedures exist for learning the parameters (Binder et al., 1997a(30); Ghahramani, 1998)(31) and structures (Friedman et al., 1998)(32) of DBNs. Norvig I 606 Data association: Data association for multi target tracking was first described in a probabilistic setting by Sittler (1964)(33). The first practical algorithm for large-scale problems was the “multiple hypothesis tracker” or MHT algorithm (Reid, 1979)(34). Many important papers are collected by Bar-Shalom and Fortmann (1988)(35) and Bar-Shalom (1992)(36). The development of an MCMC algorithm for data association is due to Pasula et al. (1999)(37), who applied it to traffic surveillance problems. Oh et al. (2009)(38) provide a formal analysis and extensive experimental comparisons to other methods. Schulz et al. (2003)(39) describe a data association method based on particle filtering. Ingemar Cox analyzed the complexity of data association (Cox, 1993(40); Cox and Hingorani, 1994(41)) and brought the topic to the attention of the vision community. He also noted the applicability of the polynomial-time Hungarian algorithm to the problem of finding most-likely assignments, which had long been considered an intractable problem in the tracking community. The algorithm itself was published by Kuhn (1955)(42), based on translations of papers published in 1931 by two Hungarian mathematicians, Dénes König and Jenö Egerváry. The basic theorem had been derived previously, however, in an unpublished Latin manuscript by the famous Prussian mathematician Carl Gustav Jacobi (1804–1851). 1. Gauss, C. F. (1829). Beiträge zur Theorie der algebraischen Gleichungen. Collected in Werke, Vol. 3, pages 71–102. K. Gesellschaft Wissenschaft, Göttingen, Germany, 1876. 2. Markov, A. A. (1913). An example of statistical investigation in the text of “Eugene Onegin” illustrating coupling of “tests” in chains. Proc. Academy of Sciences of St. Petersburg, 7. 3. Levin, D. A., Peres, Y., and Wilmer, E. L. (2008). Markov Chains and Mixing Times. American Mathematical Society. 4. Wiener, N. (1942). The extrapolation, interpolation, and smoothing of stationary time series. Osrd 370, Report to the Services 19, Research Project DIC-6037, MIT. 5. Kolmogorov, A. N. (1941). Interpolation und Extrapolation von stationären zufälligen Folgen. Bulletin of the Academy of Sciences of the USSR, Ser. Math. 5, 3–14. 6. Swerling, P. (1959). First order error propagation in a stagewise smoothing procedure for satellite observations. J. Astronautical Sciences, 6, 46–52. 7. Kalman, R. (1960). A new approach to linear filtering and prediction problems. J. Basic Engineering, 82, 35–46. 8. Baum, L. E. and Petrie, T. (1966). Statistical inference for probabilistic functions of finite state Markov chains. Annals of Mathematical Statistics, 41. 9. Viterbi, A. J. (1967). Error bounds for convolutional codes and an asymptotically optimum decoding algorithm. IEEE Transactions on Information Theory, 13(2), 260–269. 10. Rauch, H. E., Tung, F., and Striebel, C. T. (1965). Maximum likelihood estimates of linear dynamic systems. AIAA Journal, 3(8), 1445–1450. 11. Dempster, A. P., Laird, N., and Rubin, D. (1977). Maximum likelihood from incomplete data via the EM algorithm. J. Royal Statistical Society, 39 (Series B), 1–38. 12. Dean, T. and Kanazawa, K. (1989b). A model for reasoning about persistence and causation. Computational Intelligence, 5(3), 142–150. 13. Nicholson, A. and Brady, J. M. (1992). The data association problem when monitoring robot vehicles using dynamic belief networks. In ECAI-92, pp. 689–693. 14. Kjaerulff, U. (1992). A computational scheme for reasoning in dynamic probabilistic networks. In UAI-92, pp. 121–129. 15. Dean, T. and Wellman, M. P. (1991). Planning and Control. Morgan Kaufmann. 16. Murphy, K. (2002). Dynamic Bayesian Networks: Representation, Inference and Learning. Ph.D. thesis, UC Berkeley 17. Huang, T., Koller, D., Malik, J., Ogasawara, G., Rao, B., Russell, S. J., and Weber, J. (1994). Automatic symbolic traffic scene analysis using belief networks. In AAAI-94, pp. 966–972 18. Intille, S. and Bobick, A. (1999). A framework for recognizing multi-agent action from visual evidence. In AAAI-99, pp. 518-525. 19. Zweig, G. and Russell, S. J. (1998). Speech recognition with dynamic Bayesian networks. In AAAI-98, pp. 173–180. 20. Richardson, M., Bilmes, J., and Diorio, C. (2000). Hidden-articulator Markov models: Performance improvements and robustness to noise. In ICASSP-00. 21. Stephenson, T., Bourlard, H., Bengio, S., and Morris, A. (2000). Automatic speech recognition using dynamic bayesian networks with both acoustic and articulatory features. In ICSLP-00, pp. 951-954. 22. Nefian, A., Liang, L., Pi, X., Liu, X., and Murphy, K. (2002). Dynamic bayesian networks for audiovisual speech recognition. EURASIP, Journal of Applied Signal Processing, 11, 1–15. 23. Livescu, K., Glass, J., and Bilmes, J. (2003). Hidden feature modeling for speech recognition using dynamic Bayesian networks. In EUROSPEECH-2003, pp. 2529-2532 24. Murphy, K. and Mian, I. S. (1999). Modelling gene expression data using Bayesian networks. people.cs.ubc.ca/˜murphyk/Papers/ismb99.pdf. 25. Perrin, B. E., Ralaivola, L., and Mazurie, A. (2003). Gene networks inference using dynamic Bayesian networks. Bioinformatics, 19, II 138-II 148. 26. Husmeier, D. (2003). Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic bayesian networks. Bioinformatics, 19(17), 2271-2282. 27. Theocharous, G., Murphy, K., and Kaelbling, L. P. (2004). Representing hierarchical POMDPs as DBNs for multi-scale robot localization. In ICRA-04. 28. Smyth, P., Heckerman, D., and Jordan, M. I. (1997). Probabilistic independence networks for hidden Markov probability models. Neural Computation, 9(2), 227-269. 29. Roweis, S. T. and Ghahramani, Z. (1999). A unifying review of Linear GaussianModels. Neural Computation, 11(2), 305-345. 30. Binder, J., Koller, D., Russell, S. J., and Kanazawa, K. (1997a). Adaptive probabilistic networks with hidden variables. Machine Learning, 29, 213-244. 31. Ghahramani, Z. (1998). Learning dynamic bayesian networks. In Adaptive Processing of Sequences and Data Structures, pp. 168–197. 32. Friedman, N., Murphy, K., and Russell, S. J. (1998). Learning the structure of dynamic probabilistic networks. In UAI-98. 33. Sittler, R. W. (1964). An optimal data association problem in surveillance theory. IEEE Transactions on Military Electronics, 8(2), 125-139. 34. Reid, D. B. (1979). An algorithm for tracking multiple targets. IEEE Trans. Automatic Control, 24(6), 843–854. 35. Bar-Shalom, Y. and Fortmann, T. E. (1988). Tracking and Data Association. Academic Press. 36. Bar-Shalom, Y. (Ed.). (1992). Multi target multi sensor tracking: Advanced applications. Artech House. 37. Pasula, H., Russell, S. J., Ostland, M., and Ritov, Y. (1999). Tracking many objects with many sensors. In IJCAI-99. 38. Oh, S., Russell, S. J., and Sastry, S. (2009). Markov chain Monte Carlo data association for multi-target tracking. IEEE Transactions on Automatic Control, 54(3), 481-497. 39. Schulz, D., Burgard, W., Fox, D., and Cremers, A. B. (2003). People tracking with mobile robots using sample-based joint probabilistic data association filters. Int. J. Robotics Research, 22(2), 99-116 40. Cox, I. (1993). A review of statistical data association techniques for motion correspondence. IJCV, 10, 53–66. 41 Cox, I. and Hingorani, S. L. (1994). An efficient implementation and evaluation of Reid’s multiple hypothesis tracking algorithm for visual tracking. In ICPR-94, Vol. 1, pp. 437-442. 42. Kuhn, H. W. (1955). The Hungarian method for the assignment problem. Naval Research Logistics Quarterly, 2, 83-97. |
Norvig I Peter Norvig Stuart J. Russell Artificial Intelligence: A Modern Approach Upper Saddle River, NJ 2010 |
| Computer Model | Rorty | I 259 Vs Analogy Brain/Computer/Rorty: this Analogy is trivial, because a program only codifies a set of operations, and explains thinking as little as a set of logical formulas explains the laws of inference. A code adds nothing! (No additional insight). >Computation. I 262 Rorty (referring to Dodwell): As long as we are at the level of subroutines, we cannot be attributed to specified intelligence and character. No more than the talk of "red sensations" determines the assumption of internally red entities. However, if we ascend to the hardware level, the anthropomorphism is no longer appropriate. >Computer model/Dodwell. If we restricted ourselves to the hardware level, sensations would play no role anymore. Then, the computer analogy is no longer relevant, as little as with unicellular organisms. Complicated physiology arouses the need for psychology! I 263 RortyVsComputer Model (Hardware/Software): depends on the choice of the level of abstraction I 281 Question: how can the computer figure out that the current patterns flowing through the wire are the sum of the cash earnings of the day? ((s) This is determined only from the outside as an interpretation.) Rorty: it is not about studying the mode of operation at all. We will not clarify whether we should concede robots personal rights by better exploring how they work. >Robots. VI 184f Computer/Pragmatism: The question of whether computers have consciousness, which is so important for Searle and Thomas Nagel, does not even arise for pragmatism. >Artificial consciousness, >Pragmatism. The only form to confront of the world is the same for people as for computers. Cf. >Artificial Intelligence. |
Rorty I Richard Rorty Philosophy and the Mirror of Nature, Princeton/NJ 1979 German Edition: Der Spiegel der Natur Frankfurt 1997 Rorty II Richard Rorty Philosophie & die Zukunft Frankfurt 2000 Rorty II (b) Richard Rorty "Habermas, Derrida and the Functions of Philosophy", in: R. Rorty, Truth and Progress. Philosophical Papers III, Cambridge/MA 1998 In Philosophie & die Zukunft, Frankfurt/M. 2000 Rorty II (c) Richard Rorty Analytic and Conversational Philosophy Conference fee "Philosophy and the other hgumanities", Stanford Humanities Center 1998 In Philosophie & die Zukunft, Frankfurt/M. 2000 Rorty II (d) Richard Rorty Justice as a Larger Loyalty, in: Ronald Bontekoe/Marietta Stepanians (eds.) Justice and Democracy. Cross-cultural Perspectives, University of Hawaii 1997 In Philosophie & die Zukunft, Frankfurt/M. 2000 Rorty II (e) Richard Rorty Spinoza, Pragmatismus und die Liebe zur Weisheit, Revised Spinoza Lecture April 1997, University of Amsterdam In Philosophie & die Zukunft, Frankfurt/M. 2000 Rorty II (f) Richard Rorty "Sein, das verstanden werden kann, ist Sprache", keynote lecture for Gadamer’ s 100th birthday, University of Heidelberg In Philosophie & die Zukunft, Frankfurt/M. 2000 Rorty II (g) Richard Rorty "Wild Orchids and Trotzky", in: Wild Orchids and Trotzky: Messages form American Universities ed. Mark Edmundson, New York 1993 In Philosophie & die Zukunft, Frankfurt/M. 2000 Rorty III Richard Rorty Contingency, Irony, and solidarity, Chambridge/MA 1989 German Edition: Kontingenz, Ironie und Solidarität Frankfurt 1992 Rorty IV (a) Richard Rorty "is Philosophy a Natural Kind?", in: R. Rorty, Objectivity, Relativism, and Truth. Philosophical Papers Vol. I, Cambridge/Ma 1991, pp. 46-62 In Eine Kultur ohne Zentrum, Stuttgart 1993 Rorty IV (b) Richard Rorty "Non-Reductive Physicalism" in: R. Rorty, Objectivity, Relativism, and Truth. Philosophical Papers Vol. I, Cambridge/Ma 1991, pp. 113-125 In Eine Kultur ohne Zentrum, Stuttgart 1993 Rorty IV (c) Richard Rorty "Heidegger, Kundera and Dickens" in: R. Rorty, Essays on Heidegger and Others. Philosophical Papers Vol. 2, Cambridge/MA 1991, pp. 66-82 In Eine Kultur ohne Zentrum, Stuttgart 1993 Rorty IV (d) Richard Rorty "Deconstruction and Circumvention" in: R. Rorty, Essays on Heidegger and Others. Philosophical Papers Vol. 2, Cambridge/MA 1991, pp. 85-106 In Eine Kultur ohne Zentrum, Stuttgart 1993 Rorty V (a) R. Rorty "Solidarity of Objectivity", Howison Lecture, University of California, Berkeley, January 1983 In Solidarität oder Objektivität?, Stuttgart 1998 Rorty V (b) Richard Rorty "Freud and Moral Reflection", Edith Weigert Lecture, Forum on Psychiatry and the Humanities, Washington School of Psychiatry, Oct. 19th 1984 In Solidarität oder Objektivität?, Stuttgart 1988 Rorty V (c) Richard Rorty The Priority of Democracy to Philosophy, in: John P. Reeder & Gene Outka (eds.), Prospects for a Common Morality. Princeton University Press. pp. 254-278 (1992) In Solidarität oder Objektivität?, Stuttgart 1988 Rorty VI Richard Rorty Truth and Progress, Cambridge/MA 1998 German Edition: Wahrheit und Fortschritt Frankfurt 2000 |
| Constants | Mates | I 61 Predicates/Mates: predicates are constants. Cf. >Variables, >Predicates, >Predication, >Logic, >Logical Form, >Logical Formulas, >Individual Constants, >Nouns, >Singular Terms, >Names, >Objects. |
Mate I B. Mates Elementare Logik Göttingen 1969 Mate II B. Mates Skeptical Essays Chicago 1981 |
| Correctness | Logic Texts | II 109 Def correct/correctness/propositional logic/Hoyningen-Huene: be A and B statement logical formulas. The conclusion from A to B is called propositionally correct, exactly when A > B is propositionally true. II 110 The trick is that in [the above] definition the required propositional truth of A > B means different things, depending on whether A > B is a statement or a propositional formula. >Formula, >Statement, >Proposition, >Truth, >Logical truth. |
Logic Texts Me I Albert Menne Folgerichtig Denken Darmstadt 1988 HH II Hoyningen-Huene Formale Logik, Stuttgart 1998 Re III Stephen Read Philosophie der Logik Hamburg 1997 Sal IV Wesley C. Salmon Logic, Englewood Cliffs, New Jersey 1973 - German: Logik Stuttgart 1983 Sai V R.M.Sainsbury Paradoxes, Cambridge/New York/Melbourne 1995 - German: Paradoxien Stuttgart 2001 |
| Decidability | Logic Texts | Hoyningen-Huene II 227 Decidability/undecidability/decision problem: propositional logic: is decidable and complete. Predicate logic: undecidable. There is no mechanical method by which for any predicate-logical formula, the decision can be brought about whether it is universally valid or not. >Validity, >Proof. |
Logic Texts Me I Albert Menne Folgerichtig Denken Darmstadt 1988 HH II Hoyningen-Huene Formale Logik, Stuttgart 1998 Re III Stephen Read Philosophie der Logik Hamburg 1997 Sal IV Wesley C. Salmon Logic, Englewood Cliffs, New Jersey 1973 - German: Logik Stuttgart 1983 Sai V R.M.Sainsbury Paradoxes, Cambridge/New York/Melbourne 1995 - German: Paradoxien Stuttgart 2001 |
| Deduction Theorem | Berka | I 112 Def "Deduction Theorem"/Hilbert: if from a formula A a formula B is derivable in such a way that every free variable occurring in A is held fixed. i.e. that it is neither used for an insertion to be made for it nor as a distinguished variable of one of the schemes (α), (β), then the formula A > B is derivable without using the formula A. ((s) elimination of the premise). >Premises, >Deduction, cf. >Induction, >Logical formula, >Derivation, >Derivability, >Elimination, >Eliminability, >Variables. |
Berka I Karel Berka Lothar Kreiser Logik Texte Berlin 1983 |
| Definitions | Mates | I 248 Definitions/Mates: we need them to represent formalized theories. - They introduce designations that do not belong to the vocabulary of the language, but make them more readable. >Theories, >Formulas, >Logical formulas, >Theoretical language, >Theoretical terms, >Theoretical entities, >Definitions, >Definability. I 250 Def Creative Definition/Mates: leads to new theorems in which the defined symbol does not occur. >Symbols. Requirement: a satisfactory definition should be non-creative. >Vocabulary/Mates. I 248 Metalinguistic definitions/Mates: Metalinguistic definitions bring a name of the defined symbol in object language: the symbol itself - e.g. a) metalinguistically: if a and b are terms so is a = b for I21ab b) object-language: (x) (y) (x = y I21xy). >Metalanguage, >Object language, >Identity, >Definition/Frege, >Symbolic use. |
Mate I B. Mates Elementare Logik Göttingen 1969 Mate II B. Mates Skeptical Essays Chicago 1981 |
| Equivalence | Wessel | I 50 Bisubjunction/(biconditional)/Wessel: a biconditional is an operator that makes one formula out of two. >Formulas, >Logical formulas, >Operators. >Contrary to this: Equivalence: an equivalence isno Operator, but a sentence which asserts the equivalence of two formulas. >Assertions, The formulas are not even in the equivalence but quoted: "Formula A" ⇔ "formula B". >Statements, >Mention, >Quotation, >Levels/order. |
Wessel I H. Wessel Logik Berlin 1999 |
| Formalization | Wolfram | Brockman I 275 Formalization/language/Wolfram: In the late 1600s, Gottfried Leibniz, John Wilkins, and others were concerned with what they called philosophical languages—that is, complete, universal, symbolic representations of things in the world. >G. W. Leibniz, >Formal language, >Ideal language, cf. >Formal speech, >Understanding, >Logical Formulas, >Formulas. It’s interesting to see how a philosophical language of today would differ from a philosophical language of the mid-1600s. It’s a measure of our progress. In mathematics, for example: Whitehead and Russell’s Principia Mathematica in 1910 was the biggest show off effort. There were previous attempts by Gottlob Frege and Giuseppe Peano that were a little more modest in their presentation. >G. Frege, >B. Russell. WolframVsRussell/WolframVsFrege/WolframVsPeano/WolframVsLeibniz: Ultimately, they were wrong in what they thought they should formalize: They thought they should formalize some process of mathematical proof, which turns out not to be what most people care about. >Proofs, >Provability, >Systems, >Computer languages, >Computer programming. Wolfram, Stephen (2015) „Artificial Intelligence and the Future of Civilization” (edited live interview), in: Brockman, John (ed.) 2019. Twenty-Five Ways of Looking at AI. New York: Penguin Press. |
Brockman I John Brockman Possible Minds: Twenty-Five Ways of Looking at AI New York 2019 |
| Forms | Schröter | I Berka 415 Formalization/Schröter always leads to linear strings of characters.(1) >Formalization, >Formulas, >Logical formulas, >Signs. 1. K. Schröter, Was ist eine mathematische Theorie?, Jahresbericht der deutschen Mathematikervereinigung 53 (1943), 69-82 |
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| Implication | Logic Texts | II 109 Implication: Instead of a logically correct conclusion, one also speaks of a valid or deductive conclusion, instead of conclusion one also speaks of implication. The premises imply the conclusion. Def correct/correctness/statement logic/Hoyningen-Huene: be A and B statement logical formulas. The conclusion from A to B is called propositionally correct, exactly when A > B is propositionally true. >Correctness. II 110 The trick is that in [the above] definition the required propositional truth of A > B means different things, depending on whether A > B is a statement or a propositional formula. >Statement, >Formula. |
Logic Texts Me I Albert Menne Folgerichtig Denken Darmstadt 1988 HH II Hoyningen-Huene Formale Logik, Stuttgart 1998 Re III Stephen Read Philosophie der Logik Hamburg 1997 Sal IV Wesley C. Salmon Logic, Englewood Cliffs, New Jersey 1973 - German: Logik Stuttgart 1983 Sai V R.M.Sainsbury Paradoxes, Cambridge/New York/Melbourne 1995 - German: Paradoxien Stuttgart 2001 |
| Index Words | Peirce | Berka I 29 Index/indicator/Peirce: E.g. pointing finger - the physical evidence: does not say anything, it just says "there!" >Indexicality, >Ostension, >Pointing, >Ostensive definition. Berka I 30 Conclusion/Peirce: needs in addition to symbol (for truth) and index (both together (for sentence formation) the 3rd character: the icon: because inference consists in the observation that where certain relations exist, some other relations can be found. >Conclusion, >Symbols, >Icons, >Relations. These relations must be represented by an icon - e.g. the middle term of the syllogism must actually occur in both premises.(1) >Syllogisms, >Premises. Berka I 31 E.g. the empty spaces that must be filled with the symbols (x, y, ...) are indices of symbols.(1) >Variables, >Constants, Individual variables, >Individual constants, >Logical operations, >Logical formulas. 1. Ch. S. Peirce, On the algebra of logic. A contribution to the philosophy of notation. American Journal of Mathematics 7 (1885), pp. 180-202 – Neudruck in: Peirce, Ch. S., Collected Papers ed. C. Hartstone/P. Weiss/A. W. Burks, Cambridge/MA 1931-1958, Vol. III, pp. 210-249 |
Peir I Ch. S. Peirce Philosophical Writings 2011 Berka I Karel Berka Lothar Kreiser Logik Texte Berlin 1983 |
| Inserting | Logic Texts | II 133 Insertion/substitution/identity/truth preservation: Logical equivalence is (...) a weakening of the identity of statements. Logically equivalent statements are not the same in all properties, but only in logical terms. If one statement is logically true, so is the other and vice versa. If a certain statement follows logically from one, then it follows logically from the other and vice versa. >Substitution, >Substitution (Insertion), >Equivalence, >Logical truth. Insertion Theorem: Let FA be a propositional logical formula which contains a partial form A. Let FB be a formula which results from FA when A is replaced by a propositional formula B, (not necessarily everywhere). If A is now ≡ B, then FA ≡ FB applies. II 134 Logically equivalent formulas have the same inference sets. Logically equivalent formulas can be inferred from the same prerequisites. Redundancy Theory/Hoyningen-Huene: therefore, in propositional logic one does not really have to distinguish between "A" and "It is true that A". (In propositional logic such properties are abstracted from). >Redundancy theory, >Propositional logic. |
Logic Texts Me I Albert Menne Folgerichtig Denken Darmstadt 1988 HH II Hoyningen-Huene Formale Logik, Stuttgart 1998 Re III Stephen Read Philosophie der Logik Hamburg 1997 Sal IV Wesley C. Salmon Logic, Englewood Cliffs, New Jersey 1973 - German: Logik Stuttgart 1983 Sai V R.M.Sainsbury Paradoxes, Cambridge/New York/Melbourne 1995 - German: Paradoxien Stuttgart 2001 |
| Loewenheim | Hilbert | Berka I 340 Loewenheim/Hilbert/Ackermann: Loewenheim has shown that every expression that is universal for the countable domain has the same property for every other domain. In Loewenheim, however, the sentence appears in the dual version: Every formula of the function calculus is either contradictory or can be satisfied within a countable infinite range of thought. >Satisfaction, >Satisfiability, >Models, >Model theory, >Functional calculus, >Countability. General Validity/Hilbert/Ackermann: examples of formulas which are valid in each domain are all formulas that can be proved from axioms of a system. >Validity, >Universal validity. Loewenheim/Hilbert/Ackermann: Loewenheim has made another remarkable proposition: in the treatment of the logical formulas one can restrict oneself to those in which only function symbols with a maximum of two vacancies occur(1). This corresponds to: Schroeder: the general relative calculus can be traced back to the binary calculus(2). >Logical formulas. 1. L. Löwenheim: Über Möglichkeiten im Relativkalkül, Math. Annalen 76 (1915), pp. 447-470, p. 459. 2. D. Hilbert & W. Ackermann: Grundzüge der Theoretischen Logik, Berlin, 6. Aufl. Berlin/Göttingen/Heidelberg 1972, § 12. |
Berka I Karel Berka Lothar Kreiser Logik Texte Berlin 1983 |
| Logic | Logic: logic is the doctrine of the admissibility or inadmissibility of relations between statements and thus the validity of the compositions of these statements. In particular, the question is whether conclusions can be obtained from certain presuppositions such as premises or antecedents. Logical formulas are not interpreted at first. Only the interpretation, i. e. the insertion of values, e.g. objects instead of the free variables, makes the question of their truth meaningful. |
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| Logic | Lorenzen | Berka I187 Operational logic/dialogical/Lorenzen/Berka: Variant of the constructivist interpretation of intuitionism. >Intuitionism, >Dialogical Logic. Functors and quantifiers are constructively defined with regard to a dialogue game. >Functors, >Quantifiers. Truth-functions: can then be proved as sentences about the dialogic use of the functions. >Truth functions. I 188 N.B.: the successful defense of a formula in dialogue is not sufficient to prove the effective logical truth (logical validity) of this formula. For this proof it must be shown that the formula can be successfully defended against any possible strategy of the opponent. >Proofs, >Provability, >Validity, >Universal validity, >Logical formula. --- Thiel I 103 Logic/Lorenzen: It was only in the sixties that a construction of logic was developed, which can also be described as a justification in scientific theory and in a philosophical sense. It provides a possibility, not yet seen, for the justification of both the classical and the constructive concept of the "validity" of logical propositions. (Lorenzens' "dialogical logic" with proponent and opponent, also "argumentation-theoretical structure of logic"). It is supposed to show that the axiomatic derivation does not constitute the whole meaning of the proof, but that a proof should provide reasons for the truth or validity of the proved proposition. .. + .. I 105. >Axioms, >Derivation, >Derivability. |
Lorn I P. Lorenzen Constructive Philosophy Cambridge 1987 T I Chr. Thiel Philosophie und Mathematik Darmstadt 1995 |
| Mention | Mention philosophy: the mention of linguistic objects must be distinguished from their use. This distinction is sometimes difficult when symbols are partly used and partly mentioned within logical formulas. One simple case of a mention of a word or phrase is the quote. See also object language, metalanguage, quote, reference, occurrence, type, token. |
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| Models | Models, philosophy, logic: A model is obtained when a logical formula provides true statements by inserting objects instead of the free variables. One problem is the exclusion of unintended models. See also model theory. |
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| Operators | Wessel | I 1 logical operators/Wessel: e.g. and, not, or, all, some, "the fact that", "the non-fact that". >Connectives, >Logical constants. Terms/Wessel: e.g "the fact that metals conduct electricity ’"H2O", "brother and sister", "divisible by three" ... No terms are: and, all, in, or, "the earth revolves around the sun". I 131 Operator/Wessel: must not occur more than once in provable formulas of propositional logic. >Propositional logic, >Proofs, >Provability, >Logical formulas. ((s)Operator/(s): (e.g. subjunction) does not lead to paradoxes, because it is not "predicated of something" like predicates (implication). ((s) Operator / (s): rather purely formal - in contrast: predicate: content). >Predicates, >Predication. |
Wessel I H. Wessel Logik Berlin 1999 |
| Predicates | Predicates, philosophy, logic: predicates are symbols that can stand in logical formulas for properties. In fact, not every predicate stands for a property, since it has contradictory predicates, but no contradictory properties. For example, one can think of a predicate "squaround" for "square and round", that is, two properties that exclude each other. One can then truthfully say "Nothing is squaround". There are therefore more predicates than properties. See also round square, scheme characters, quantification, 2nd level logic, predication, attributes, adjectives. |
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| Predicates | Mates | I 61 Predicates/Mates: Predicates are constants. Cf. >Variables, >Predication, >Logic, >Logical form, >Logical formulas, >Individual constants, >Nouns, >Singular Terms, >Names, >Objects. |
Mate I B. Mates Elementare Logik Göttingen 1969 Mate II B. Mates Skeptical Essays Chicago 1981 |
| Quantifiers | Wessel | I 153 Quantifier/Wessel: a quantifier refers to terms within statements. >Terms, >Logical formulas, >Statements, >Quantification. |
Wessel I H. Wessel Logik Berlin 1999 |
| Rules | Wessel | I 48 Laws/rules/logic/Wessel: Law = tautologies with operators. >Laws, >Tautologies, >Operators. I 50f Rules: sentences about formulas (the formulas are even not present as formulas but as quotations) = equivalences. >Quote/disquotation, >Levels/order, >Description levels, >Formulas, >Logical formulas. "Equivalence" is not an operator. >Equivalence. |
Wessel I H. Wessel Logik Berlin 1999 |
| Scope | Scope, range, logic, philosophy: range is a property of quantifiers or operators to be able to be applied to a larger or smaller range. For example, the necessity operator N may be at different points of a logical formula. Depending on the positioning, the resulting statement has a considerably changed meaning. E.g. great range "It is necessary that there is an object that ..." or small range "There is an object that is necessarily ....". See also quantifiers, operators, general invariability, stronger/weaker, necessity, Barcan Formula. |
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| Strength of Theories | Hintikka | II 7 Standard Semantics/Kripke Semantics/Hintikka: what differences are there? The ditch between standard semantics and Kripke semantics is much deeper than it first appears. Cocchiarella: Cocchiarella has shown, however, that even in the simplest quantifying case of the monadic predicate logic, the standard logic is radically different from its Kripke cousin. Decidability: monadic predicate logic is, as Kripke has shown, decidable. Kripke semantics: Kripke semantics is undecidable. Decisibility: Decisibility implies axiomatizability. Stronger/weaker/Hintikka: as soon as we go beyond monadic predicate logic, we have a logic of considerable strength, complexity, and unruliness. Quantified standard modal logic of the 1. level/Hintikka: the quantified standard modal logic of the 1. level is in a sense more powerful than the 2. level logic (with standard semantics). The latter is, of course, already very strong, so that some of the most difficult unresolved logical and quantum-theoretical problems can be expressed in terms of logical truth (or fulfillment) in logical formulas of the second level. Def equally strong/stronger/weaker/Hintikka: (here): the terms "stronger" and "weaker" are used to show an equally difficult decision-making problem. Decision problem: the standard logic of the 2. level can be reduced to that for quantified standard modal logic of the 1. level. Reduction: this reduction is weaker than translatability. II 9 Quantified standard modal logic of the 1. level/Hintikka: this logic is very strong, comparable in strength with the 2. level logic. It follows that it is not axiomatizable (HintikkaVsKripke). The stronger a logic is, the less manageable it is. II 28 Branching Quantifiers/stronger/weaker/Hintikka: E.g. branching here: 1. Branch: there is an x and b knows... 2. Branch: b knows there is an x ... Quantification with branched quantifiers is extremely strong, almost as strong as 2. level logic. Therefore, it cannot be completely axiomatized (quantified epistemic logic with unlimited independence). II 29 Variant: variants are simpler cases where the independence refers to ignorance, combined with a move with a single, non-negated operator {b} K. Here, an explicit treatment is possible. II 118 Seeing/stronger/weaker/logical form/Hintikka: a) stronger: recognizing, recognizing as, seeing as. b) weaker: to look at, to keep a glance on, etc. Weaker/logical form/seeing/knowing/Hintikka: e.g. (Perspective, "Ex") (15) (Ex) ((x = b) & (Ey) John sees that (x = y)). (16) (Ex)(x = b & (Ey) John remembers that x = y)) (17) (Ex)(x = b & (Ey) KJohn (x = y)) Acquaintance/N.B.: in (17) b can be John's acquaintance even if John does not know b as b! ((S) because of y). II 123 Everyday Language/ambiguity/Hintikka: the following expression is ambiguous: (32) I see d Stronger: (33) (Ex) I see that (d = x) That says the same as (31) if the information is visual or weaker: (34) (Ex) (d = x & (Ey) I see that (x = y)) This is the most natural translation of (32). Weaker: for the truth of (34) it is enough that my eyes simply rest on the object d. I do not need to recognize it as d. |
Hintikka I Jaakko Hintikka Merrill B. Hintikka Investigating Wittgenstein German Edition: Untersuchungen zu Wittgenstein Frankfurt 1996 Hintikka II Jaakko Hintikka Merrill B. Hintikka The Logic of Epistemology and the Epistemology of Logic Dordrecht 1989 |
| Truth Value Gaps | Wessel | I 157 Truth-value gaps/Wessel: if the object does not exist. >Non-existence. Prior: "unstatable": third value. >Truth values/Prior. Composite formulas: not discardable, because value can not be determined. Cf. >Compositionality, >Complexity, >Formulas, >Logical formulas. |
Wessel I H. Wessel Logik Berlin 1999 |
| Use | Use, philosophy: words are used to mention something. The distinction use/mention is important in the philosophy of language because words or phrases in turn may be mentioned, as in a quote or a correction. Within logical formulas parts are used, others are mentioned. See also mentioning, use theory, meaning, meaning theory, language, quote/disquotation, quotation marks, quasi-quotation, object language, metalanguage. |
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| Variables | Mates | I 36 Variable/Mates: for them names or descriptions are used. >Names, >Descriptions, >Inserting. Values: values include all objects, which can be designated by these expressions (according to a convention). >Naming, >Denotation, >Domains. I 37 no changeable things, also no names of changeable things. >Numbers/Frege, >Variables/Frege. I 66 Variable/free/bound/Mates: E.g. "(x)F"x": here bound for the second time. Problem: simultaneously within "F"x" free. - ((S) considered without quantifier. >Bound variables, >Free variables, >Quantifiers, >Quantification. I 67 and formulas (if used) may occur bound. >Logical formulas. I 68 (s) An entire formula always occurs free of course. Cf. >Free-standing content/Brandom, cf. >Generalization/Mates. |
Mate I B. Mates Elementare Logik Göttingen 1969 Mate II B. Mates Skeptical Essays Chicago 1981 |
| Variables | Schönfinkel | Berka I 277 Def Variable/Schönfinkel: A variable is nothing more than a badge to mark certain places for arguments and operators as belonging together. - So that it has the character of a bare, the constant nature of a actually unreasonable, auxiliary concept.(1) >Symbols, >Signs, >Formulas, >Logical formulas, >Constants, >Logical constants, >Placeholder. 1. M. Schönfinkel, Über die Bausteine der mathematischen Logik, Math. Ann. 92 (1924), 305-316 |
Berka I Karel Berka Lothar Kreiser Logik Texte Berlin 1983 |
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| Disputed term/author/ism | Author Vs Author |
Entry |
Reference |
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| Dodwell, P.C. | Rorty Vs Dodwell, P.C. | I 258 Dodwell/Rorty: what would someone like Dodwell answer to this argument? Dodwell pro analogy brain/computer. >Computation, >Computer Model. I 259 VsAnalogy Brain/Computer/Computation/RortyVsDodwell/VsAnalogies/Rorty: this analogy is trivial, because a program only codifies a set of operations and explains thinking as little as a set of logical formulas explain the laws of inference. F.o.th. a code adds nothing! (No additional insight). Dodwell: the analogy only becomes mandatory when different levels are distinguished. Hardware/Software. Conceptual level: "control process" - physiological level: hardware. The principle of operation of the subprograms cannot in turn be made understood by studying the hardware. Accordingly, the understanding how the subprograms themselves work does not help us to explain the principle of problem solving in the terminology of a sequence of steps. This requires consideration of the control process that embodies the overall organization of the machine. I 259 Analogy Brain/Computer/Computation/RortyVsDodwell/Rorty: trivial: a program may also be assumed for thinking - Dodwell: you have to assume different levels - (hardware/software) - the principle of subprograms cannot be understood by studying the hardware - solution: control process which embodies the overall organization of the machine - Analogy: in reality we do not recognize visual patterns not through selection of critical features, but by finding and comparing matching templates. This is neither a "conceptual" statement (about the "control process") nor a "physiological" statement (about the "hardware"), but nevertheless has a genuine explanatory value. I 260 The idea of a "subprogram" seems to give us precisely what psychology needs, an explanation that might be good for this tertium quid between common sense and physiology. Rorty: how does this help us against the regress arguments, though? Malcolm and Ryle would probably insist that the "templates" in turn bring up the same issues as the "consistency" which is to be explained by them. DodwellVsRyle: but that would only be the case if they were to serve to answer such general questions like "how is abstraction (recognition, constancy) possible?". But there are no answers to such questions apart from the pointless remark that nature had produced the appropriate material to such achievements! Wittgenstein similar: the fact that rules are implicit, and in any case not all the rules can be explicit, prevents recourse. (See Rules/Brandom). Recourse/Homunculus/Rorty: I think it is misleading to say the little man (homunculus) leads to regress, because I do not see how little machines are less "conscious" than small men. We cannot explore which of these bundles are "tinted with consciousness", in Quine's words, nor whether this tint is lacking. Familiarity with computers does not lead to such a discovery, but merely turns the intentional position into something common and casual. Inferring/Subconsciously/Helmholtz/Rorty: concept of "subconsciously inferring"! Perceptions as subconscious inferences. (RyleVs). I 261 Doubling/Rorty: the complaint that the templates like Lockean ideas led to a doubling of the explanandum is like the complaint that the particles of the Bohr atom doubled the billiard balls whose behavior they help to explain. ((s) 1) inversion, 2) analogies are not doubling anyway) Rorty: It turns out, however, that it is fruitful to postulate small billiard balls inside the big billiard balls. Model/Sellars: every model has its comment aside. Psychology/Rorty: we can assume the following comment for all anthropomorphic models of psychology: As long as we are at the level of subprograms, we are not set to attribute reason and character. I 262 No more than the talk of 'red sensations' determines the assumption of internal red-colored entities. However, if we ascend to the hardware level, then anthropomorphism is no longer appropriate. If we limited ourselves to the hardware level, sensations would play no role anymore. Then the computer analogy is no longer relevant, as little as with unicellular organisms. Complicated physiology arouses the need for psychology! Dodwell: subprograms cannot in turn be made understandable by studying the hardware, just as the purpose of multiplication tables cannot be seen by examining the brain. (Also Fodor: distinction between functions (program) and mechanics (hardware) in psychology is irreducible and not merely pragmatic.) RortyVsDodwell: that is seriously misleading: it contains a confusion of the evident idea: I 263 if we did not know what multiplication is, we could not even find it out by examination of the brain With the dubious statement: Even if we knew what multiplication is, we could not find out if someone has just multiplied by examining his brain. The latter is doubtful. RortyVsDodwell: the question of what can best be explained by hardware, and what better through the programs, depends on how ad hoc or manageable the hardware in question is. Whether something is ad hoc or manageable, clearly depends on the choice of vocabulary and attraction level. And that's precisely why this is also true for the hardware/software distinction itself. Rorty: Yes, you can imagine machines whose structure can be found out easier by opening them than by looking at the programs. Rorty: the brain is almost certainly no such machine. But that it is possible with some machines is an important philosophical principle. I 263/264 It shows that the difference between psychology and physiology is no stronger difference between two subject areas than, for example, the difference between chemistry and physics. Regress/Rorty: the argument of duplication is simply due to a poorly asked question. (VsMalcolm and VsRyle "How is movement possible?" "Why does nature follow laws?"). I 265 Dodwell/Rorty: models such as that of Dodwell are not brought forward for solving Cartesian pseudo-problems, nor as discoveries about any non-physical entities. Then the argument of recourse is not valid. I 266 For the prognostic success would make it sufficiently clear that these objects of psychological research really exist. Ryle: Dilemma between learned and innate skills: RortyVsRyle: Dodwell's models allow us to admit easily that nature must have installed some innate skills in us so that we can perform our higher mental operations. At least some of the homunculi must have existed there from birth. And why not? (SearleVs). Why should subprograms in the shape of chromosomes not be incorporated? The question as to which are added later is surely not important for understanding the human nature. Psychology/Rorty: postulates "intervening variables" as a mere placeholders for undiscovered neural processes. Psychology: if it was discovered that physiology will never explain everything, it would not make psychology something dubious. I 267 Abstract/Rorty: it will not surprise us that something "abstract" like the ability to detect similarities, was not obtained, nor was the so 'concrete' ability to respond to the note C sharp. Abstract/Concrete/RortyVsFodor: the entire distinction of abstract/concrete (also Kant) is questionable. No one can say where the line is to be drawn. (Similar to the idea of the "irreducibly psychical" in contrast to the "irreducibly physical".) |
Rorty I Richard Rorty Philosophy and the Mirror of Nature, Princeton/NJ 1979 German Edition: Der Spiegel der Natur Frankfurt 1997 Rorty II Richard Rorty Philosophie & die Zukunft Frankfurt 2000 Rorty II (b) Richard Rorty "Habermas, Derrida and the Functions of Philosophy", in: R. Rorty, Truth and Progress. Philosophical Papers III, Cambridge/MA 1998 In Philosophie & die Zukunft, Frankfurt/M. 2000 Rorty II (c) Richard Rorty Analytic and Conversational Philosophy Conference fee "Philosophy and the other hgumanities", Stanford Humanities Center 1998 In Philosophie & die Zukunft, Frankfurt/M. 2000 Rorty II (d) Richard Rorty Justice as a Larger Loyalty, in: Ronald Bontekoe/Marietta Stepanians (eds.) Justice and Democracy. Cross-cultural Perspectives, University of Hawaii 1997 In Philosophie & die Zukunft, Frankfurt/M. 2000 Rorty II (e) Richard Rorty Spinoza, Pragmatismus und die Liebe zur Weisheit, Revised Spinoza Lecture April 1997, University of Amsterdam In Philosophie & die Zukunft, Frankfurt/M. 2000 Rorty II (f) Richard Rorty "Sein, das verstanden werden kann, ist Sprache", keynote lecture for Gadamer’ s 100th birthday, University of Heidelberg In Philosophie & die Zukunft, Frankfurt/M. 2000 Rorty II (g) Richard Rorty "Wild Orchids and Trotzky", in: Wild Orchids and Trotzky: Messages form American Universities ed. Mark Edmundson, New York 1993 In Philosophie & die Zukunft, Frankfurt/M. 2000 Rorty III Richard Rorty Contingency, Irony, and solidarity, Chambridge/MA 1989 German Edition: Kontingenz, Ironie und Solidarität Frankfurt 1992 Rorty IV (a) Richard Rorty "is Philosophy a Natural Kind?", in: R. Rorty, Objectivity, Relativism, and Truth. Philosophical Papers Vol. I, Cambridge/Ma 1991, pp. 46-62 In Eine Kultur ohne Zentrum, Stuttgart 1993 Rorty IV (b) Richard Rorty "Non-Reductive Physicalism" in: R. Rorty, Objectivity, Relativism, and Truth. Philosophical Papers Vol. I, Cambridge/Ma 1991, pp. 113-125 In Eine Kultur ohne Zentrum, Stuttgart 1993 Rorty IV (c) Richard Rorty "Heidegger, Kundera and Dickens" in: R. Rorty, Essays on Heidegger and Others. Philosophical Papers Vol. 2, Cambridge/MA 1991, pp. 66-82 In Eine Kultur ohne Zentrum, Stuttgart 1993 Rorty IV (d) Richard Rorty "Deconstruction and Circumvention" in: R. Rorty, Essays on Heidegger and Others. Philosophical Papers Vol. 2, Cambridge/MA 1991, pp. 85-106 In Eine Kultur ohne Zentrum, Stuttgart 1993 Rorty V (a) R. Rorty "Solidarity of Objectivity", Howison Lecture, University of California, Berkeley, January 1983 In Solidarität oder Objektivität?, Stuttgart 1998 Rorty V (b) Richard Rorty "Freud and Moral Reflection", Edith Weigert Lecture, Forum on Psychiatry and the Humanities, Washington School of Psychiatry, Oct. 19th 1984 In Solidarität oder Objektivität?, Stuttgart 1988 Rorty V (c) Richard Rorty The Priority of Democracy to Philosophy, in: John P. Reeder & Gene Outka (eds.), Prospects for a Common Morality. Princeton University Press. pp. 254-278 (1992) In Solidarität oder Objektivität?, Stuttgart 1988 Rorty VI Richard Rorty Truth and Progress, Cambridge/MA 1998 German Edition: Wahrheit und Fortschritt Frankfurt 2000 |
| Phenomenalism | Quine Vs Phenomenalism | II 57 QuineVsPhenomenalism: Our propositions typically deal with bodies and fabrics in the outside world (sic) and not with sense data. Some of these sentences, however, are triggered by stimulation of the surface. At the time of word and object any aftertaste of "sense qualities" was extinguished at the surface stimulation. People do not think or talk about the stimulation of their nerve endings. The physiological formulation was in accordance with my naturalism and the rejection of a first philosophy. |
Quine I W.V.O. Quine Word and Object, Cambridge/MA 1960 German Edition: Wort und Gegenstand Stuttgart 1980 Quine II W.V.O. Quine Theories and Things, Cambridge/MA 1986 German Edition: Theorien und Dinge Frankfurt 1985 Quine III W.V.O. Quine Methods of Logic, 4th edition Cambridge/MA 1982 German Edition: Grundzüge der Logik Frankfurt 1978 Quine V W.V.O. Quine The Roots of Reference, La Salle/Illinois 1974 German Edition: Die Wurzeln der Referenz Frankfurt 1989 Quine VI W.V.O. Quine Pursuit of Truth, Cambridge/MA 1992 German Edition: Unterwegs zur Wahrheit Paderborn 1995 Quine VII W.V.O. Quine From a logical point of view Cambridge, Mass. 1953 Quine VII (a) W. V. A. Quine On what there is In From a Logical Point of View, Cambridge, MA 1953 Quine VII (b) W. V. A. Quine Two dogmas of empiricism In From a Logical Point of View, Cambridge, MA 1953 Quine VII (c) W. V. A. Quine The problem of meaning in linguistics In From a Logical Point of View, Cambridge, MA 1953 Quine VII (d) W. V. A. Quine Identity, ostension and hypostasis In From a Logical Point of View, Cambridge, MA 1953 Quine VII (e) W. V. A. Quine New foundations for mathematical logic In From a Logical Point of View, Cambridge, MA 1953 Quine VII (f) W. V. A. Quine Logic and the reification of universals In From a Logical Point of View, Cambridge, MA 1953 Quine VII (g) W. V. A. Quine Notes on the theory of reference In From a Logical Point of View, Cambridge, MA 1953 Quine VII (h) W. V. A. Quine Reference and modality In From a Logical Point of View, Cambridge, MA 1953 Quine VII (i) W. V. A. Quine Meaning and existential inference In From a Logical Point of View, Cambridge, MA 1953 Quine VIII W.V.O. Quine Designation and Existence, in: The Journal of Philosophy 36 (1939) German Edition: Bezeichnung und Referenz In Zur Philosophie der idealen Sprache, J. Sinnreich (Hg) München 1982 Quine IX W.V.O. Quine Set Theory and its Logic, Cambridge/MA 1963 German Edition: Mengenlehre und ihre Logik Wiesbaden 1967 Quine X W.V.O. Quine The Philosophy of Logic, Cambridge/MA 1970, 1986 German Edition: Philosophie der Logik Bamberg 2005 Quine XII W.V.O. Quine Ontological Relativity and Other Essays, New York 1969 German Edition: Ontologische Relativität Frankfurt 2003 Quine XIII Willard Van Orman Quine Quiddities Cambridge/London 1987 |
| Propositions | Quine Vs Propositions | V 61 QuineVsPropositions: to maintain the old "ideas": the idea that a sentence expresses. Superfluous. VI 99 QuineVsPropositional Stances de re: peculiar intention relation between thoughts and intended things. There are no reliable policies for that. Not scientific. Better: Opinions de dicto. VI 142 Propositions/QuineVsPropositions: are not sentence meanings. This is shown by the indeterminacy of translation. X 19 Proposition/QuineVsPropositions: as meaning of sentences, as an abstract entity in its own right. Some authors: consider it as what t/f is, and between which there are implications. Oxford/Terminology: many authors use "proposition" for statements. Quine: in my earlier works I used it for assertions. I gave up on it, because of the following trend: Proposition/Oxford: actions that we perform when we express assertions. X 20 Proposition/QuineVsPropositions: their representative believes to save a step and thus to achieve immediacy: Truth/Tarski/Quine: the Englishman speaks the truth, 1) Because "Snow is white" means that snow is white and 2) Snow is white. Quine: the propositionalist saves step (1). The proposition that snow is white is simply true, because snow is white. ((s) >Horwich: "because snow..."). He bypasses differences between languages and differences between formulations within a language. Quine: my disapproval does not arise from dislike of abstract things. Rather: QuineVsPropositions: if they existed, they would bring about a certain relationship of synonymy or equivalence between propositions themselves: False Equivalence/Quine: such sentences would be equivalent that express the same proposition. QuineVsEquivalence of Sentences/VsSentence Equivalence: the equivalence relation makes no objective sense at the level of sentences. X 32 Letter/Quine: p can be schematic letter (only for sentences) or variable (then only for objects). Here problem: that does not work simultaneously! Solution: semantic ascent: we only talk about sentences. Sentence/Name/Quine: the other formulation could be given sense by stipulating that sentences are names, for example, of propositions. Some Authors: have done that. Before that, however, the letter "p" is no variable about anything except schematic letters, placeholder for sentences in a logical formula or grammatical structure. QuineVsPropositions: Problem: once sentences are conceived as names of propositions, the letter "p" is also a variable about objects, namely propositions. Then, however, we can correctly say: "p or not p' for all propositions p" ((s) Because the letter p is no longer at the same time a variable about objects and a schematic letter for sentences, but only a variable about objects.) |
Quine I W.V.O. Quine Word and Object, Cambridge/MA 1960 German Edition: Wort und Gegenstand Stuttgart 1980 |
| Various Authors | Cresswell Vs Various Authors | II 58 Computation/Cresswell: (representative: e.g. Moore/Hendrix, 1981) make it appear as if they have solved a problem which logicians have tried in vain to solve for years. CresswellVs: these are two completely different issues: ((s) The logicians are more concerned with the semantic one, the computation people with psychological issues). Content/Cresswell: (of a complement sentence) can be considered to be an equivalence class of all objects that are considered representations of this sentence. Belief objects/Moore/Hendrix (Hendrix 1981) some of these objects (the objects of mental states such as beliefs) are sentences in an internal language of the mind, others are in public language. There may be some that are in no language at all. (E.g. logical formulas). --- II 59 Content/Meaning/Cresswell: two sentences have the same meaning when they have the same content, providing they contain no index words. (5) The map indicates that the distance to Lower Moutere is 12 km. ... This requires each sentence to already have a meaning, so that the attitude is simply an attitude with regard to the meaning. CresswellVsMoore/CresswellVsHendrix: i.e. we can only solve the problem of Moore and Hendrix if we already have a semantics. Synonymy/Cresswell: if the synonymy relation ~~ (notation: in the book two swung dashes on top of each other) is defined like that, it can be set up compositionally for the whole language. I have no idea how this is supposed to work, but Hendrix and Moore refrain from it anyway. CresswellVsHendrix: they do not show how the synonymy classes are obtained. --- Hughes I 260 Non-standard systems/Hughes/Cresswell: have other basic operators as L and M. E.g. Halldén (1949b): limitation to a single three-digit operator which defines all other modal and truth-functional operators: [p, q, r] with the meaning that "either p is false or q is false or r is impossible" , i.e. (~p v ~q v ~Mr). Then: negation, conjunction, possibility: ~a = def [a,a,a] (a . b) = def [a,b[a, ~a,a]] Ma = def ~[[a, ~a,a],[a ~a,a],a] Hughes I 261 Hughes/CresswellVsHalldén: that makes an unnatural impression. |
Cr I M. J. Cresswell Semantical Essays (Possible worlds and their rivals) Dordrecht Boston 1988 Cr II M. J. Cresswell Structured Meanings Cambridge Mass. 1984 Hughes I G.E. Hughes Maxwell J. Cresswell Einführung in die Modallogik Berlin New York 1978 |
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