Methodology I HDmethod S 78 App 7 AB

Methodology I HD-method (S 7&8, App. 7 A/B, 8 A) • 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 1

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

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 3

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

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 counterexamples • Asymmetric (S 8. 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! 5

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 6

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 7

Dogmatic behavior Kuhn/Lakatos App. 8 A • 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 8 – pseudoscientific: if without PIP

Hiërarchie van epistemologische posities Q 0: onafhankelijke natuurwerkelijkheid? Nee ontologisch idealisme Ja: ontologisch realisme Q 1: ware claims mogelijk? Nee epistemologisch relativisme - ervarings-scepticisme Ja: epistemologisch realisme - inductief scepticisme Q 2: voorbij waarneembaar? Nee observational realisme - instrumentalisme Ja: wetenschappelijk realisme - constructief empiricisme Q 3: voorbij referentie? Nee referentieel realisme 9 entiteiten realisme

Vier perspectieven voor theorierealisme 10

Soorten actuele en nomische waarheidsbenadering • PM: het beste afleidingsinstrument: instrumentalist • observationeel: constructive empiricist • referentieel: referentieel realist • theoretisch: constructief realist • essentialistisch: essentialistisch realist 11 PM: “de waarheid”: de sterkste ware theorie

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 12 – everything goes sometimes

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 13

From d- to p-consequences • Idealization: H E: )consequence of H E deductive (d- • 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) 14 hence, assuming p(E)<1, a d-consequence is a p-

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 15 validity” = uncertainty conclusion sum uncertainty

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 16

From d- to p-confirmation: Conclusions Analysis ICR Part I (Si. S 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 17

Challenge • A coherent I&C explication of deductive and probabilistic methods of testing and of separate and comparative evaluation, taking counterexamples into account • testing sep. eval. comp. eval. deductive ICR probabilistic ICR/Si. S to be done ICR to be 18

HD- and HP-testing and -evaluation 19

D-/P-Evaluation Matrix (Bx: deductive boxes, ICR/Si. S) 20

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, E 2 more risky prediction of H than E 1, iff p(E 2/C) < p(E 1/C) and p(E 2/H&C) p(E 1/H&C) • assuming C, H 2 explains E better than H 1, 21 iff

Comparative Evaluation and Truth Approximation • ICR-story in terms of positive and negative HDresults: – 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) 22

Conclusion • There is a HP-method as a straightforward concretization of the HDmethod: 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 23

References Kuipers, T. (ICR/2000), From Instrumentalism to Constructive Realism, Synthese Library 287, Kluwer AP, Dordrecht, Kuipers, T. (Si. S/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 24 inference to the best explanation”, to appear in