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1 Methodology I HD-method ( S7&8, App. 7A/B, 8A) for testing and further evaluation of theories –derive and test (general and individual) test implications (in observation terms) examples –Einstein-Eddington: GRT light bending –Newell&Simon: physical symbol system hypothesis a physical symbol system has the necessary and sufficient means for general intelligent action falsification or confirmation (no verification!)

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2 Dogmatic HD-strategies: challenge ( App. 7B) auxiliary hypotheses (many types, see DN-model) validity of logico-mathematical argumentation observation presuppositions initial test conditions decision criterion (statistical/approximative) inductive jump (to general success)

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3 Separate HD-evaluation HD-method applied to theory X –derive and test general test implications –per I: ito (in terms of) individual test implications, either falsification: by individual counter example of I, and hence of X or acceptance of I: general success of X NB: success: prediction or explanation, minimal. derivable

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4 Evaluation report of X at t Negative: problems Asymmetric model: –individual counterexamples Symmetric models: –general counter-examples –indicvidual counterexamples Positive: successes –general successes –individual successes

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5 Comparative HD-evaluation Def: Y is at t more successful than X –no extra counter-examples –previous successes are retained –more successes and/or fewer counter-examples Asymmetric (S8.1), or symmetric (S.8.2) –then with (qualitative or quantitative) comparative matrix CSH: Comparative Success Hypothesis: –Y remains at least as successful as X –interesting hypothesis, even if Y is already falsified!

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6 Rule of Success (Instrumentalist):IRS IRS: If CSH has been “sufficiently” tested, choose, for the time being, the more successful theory Application of IRS: empirical progress CLAIM: IRS, and hence the HD-method, are functional for truth approximation

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7 General Methodological Principles 1) Falsifiability (= confirmability/testability) 2) Evaluation (=> evaluation report) specifically: aim at likely falsification (= potential strong confirmation!) 3) Improvement Principle (IP) (=> empirical progress) –not: elimination-principle (EP) (Popper?) –e.g. by idealization and concretization 4) For remaining choices: simplicity, and other aesthetic criteria

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8 Dogmatic behavior Kuhn/Lakatos App. 8A Improvement principle (IP) Programmatic improvement principle (PIP) –aim at a better theory with the same hard core –if necessary, adapt the hard core –if no other option, look for another program (P)IP functional for empirical progress and truth approxination Types of dogmatic behavior: –scientific: if with PIP –pseudoscientific: if without PIP

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9 Hiërarchie van epistemologische posities Q0: onafhankelijke natuurwerkelijkheid?Nee ontologisch idealisme Ja: ontologisch realisme Q1: ware claims mogelijk?Nee epistemologisch relativisme - ervarings-scepticisme Ja: epistemologisch realisme - inductief scepticisme Q2: voorbij waarneembaar?Nee observational realisme - instrumentalisme Ja: wetenschappelijk realisme - constructief empiricisme Q3: voorbij referentie?Nee referentieel realisme entiteiten realisme Ja: theorie-realisme Q4: ideale conceptualisering?Nee constructief realisme Ja: essentialistisch realisme

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10 Vier perspectieven voor theorie-realisme

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11 Soorten actuele en nomische waarheidsbenadering PM: het beste afleidingsinstrument: instrumentalist observationeel: constructive empiricist referentieel:referentieel realist theoretisch:constructief realist essentialistisch:essentialistisch realist PM: “de waarheid”: de sterkste ware theorie over een gegeven domein in een gegeven vocabulair

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12 Conclusies ICR vooruitblik: How to approach the truth? goede redenen voor overstap:instrumentalist 1 constructief empiricist 2 referentieel realist 3 constructief realist, maar niet voor 4 essentialist 1,2 3 tbv lange termijn dynamiek: theorieën als waar accepteren levert nieuwe observatietermen instrumentalistische methode efficiënter voor waarheids- benadering dan falsificationistische methode hiërarchie van heuristische posities, geen dogma –everything goes sometimes –reculer pour mieux sauter

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13 A probabilistic perspective on the hypothetical method Theo A.F. Kuipers, Groningen, www.philos.rug.nl/personae/kuipers concept explication by I&C I.e. idealization and concretization (to appear A) tested by the approximative reduction principle: AR-test, i.e. extreme special case

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14 From d- to p-consequences Idealization: H E: E deductive (d-)consequence of H Concretization: p(E/H) > p(E): E probabilistic (p-)consequence of H 1 > p(E/H) > p(E): E pp(proper p)-consequence of H AR-test: let H E, then p(E/H)=1 > p(E) hence, assuming p(E)<1, a d-consequence is a p-consequence To be studied: PCn(A) = def {B/p(B/A)>p(B)}

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15 Comparisons Not: probable consequence/validity, e.g. J.L.Cohen: The provable and the probable –mainly about Baconian vs Pascalian probabilities F. Jackson: assertability of a conditional (A B) iff p(B/A) high Perhaps: probabilistic conditional/validity, but not so e.g. R. Bradley and N. Schwartz: “B follows probably from A” = –iff most models of A are models of B E. Adams: “probability conditional” = p(B/A), and “p-validity” = uncertainty conclusion sum uncertainty premises To be checked: D. Lewis, R.C. Jeffrey, F.P. Ramsey, R. Stalnaker

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16 From the HD- to the HP-method of testing Definition E is a d-/p-test implication of H iff E is an ‘observational’ d-/p-consequence of H Idealization: Hypothetico-Deductive (HD-)Method aims at d-confirmation or falsification of d-test implications Concretization: Hypothetico-Probabilistic (HP-)Method aims at p-confirmation or p-disconfirmation of p-test implications

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17 From d- to p-confirmation: Conclusions Analysis ICR Part I (SiS Ch. 7.1.2) There is a coherent landscape of confirmation notions, allowing different languages of (degrees of) confirmation Idealization: Deductive confirmation Concretization: Probabilistic confirmation –basic definition: p(E/H)>p(E) –instead of standard: p(H/E)>p(H) –‘p’ may be Popperian: no inductive means Carnapian: only inductive likelihoods Bayesian: only inductive priors Hintikkian: both –which one, no fact of the matter

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18 Challenge A coherent I&C explication of deductive and probabilistic methods of testing and of separate and comparative evaluation, taking counterexamples into account testingsep. eval.comp. eval. deductiveICR ICR ICR probabilisticICR/SiSto be doneto be done

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19 HD- and HP-testing and -evaluation

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20 D-/P-Evaluation Matrix (Bx: deductive boxes, ICR/SiS)

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21 DN-/PN-predictions and -explanations: “H predicts/explains E, assuming C (=A&B&C)” DN-idealization H&C E PN-concretization p(E/H&C) > p(E/C) AR-test: OK assuming C, E2 more risky prediction of H than E1, iff p(E2/C) < p(E1/C) and p(E2/H&C) p(E1/H&C) assuming C, H2 explains E better than H1, iff p(E/H2&C) > p(E/H1&C)

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22 Comparative Evaluation and Truth Approximation ICR-story in terms of positive and negative HD-results: –Definition “more successfulness” –Comparative Success Hypothesis –Instrumentalist Rule of Success (IRS) –Inference to the Best Theory (IBT, to appear B) –Inductive Jump to the Best Theory (to appear B) Extendable to HP-results!?

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23 Conclusion There is a HP-method as a straightforward concretization of the HD-method: AR-tests: –all transitions from p- to d-notions: p (E/H)=1/0 –from separate evaluation to testing: not yet falsified –from comparative to separate evaluation: one tautology Depending on p: Popperian, Carnapian, Bayesian, Hintikkian Enabling: testing; separate and comparative evaluation; explanation and prediction To be further studied –similar perspectives on truth approximation –PCn(A) = def {B/p(B/A)>p(B)}

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24 References Kuipers, T. (ICR/2000), From Instrumentalism to Constructive Realism, Synthese Library 287, Kluwer AP, Dordrecht, Kuipers, T. (SiS/2001), Structures in Science, Synthese Library 301, Kluwer AP, Dordrecht, To appear A: ” Empirical and conceptual idealization and concretization. The case of truth approximation", to appear in Liber Amicorum for Leszek Nowak, homepage To appear B: ” Inference to the best theory, rather than inference to the best explanation”, to appear in Proceedings ESF-workshop Induction and Deduction in the Sciences, Vienna, 2002, homepage.

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