Upload
skye-bowns
View
214
Download
1
Tags:
Embed Size (px)
Citation preview
1
Methodology IHD-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!)
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)
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
4
Evaluation report of X at t
Negative: problems
Asymmetric model:– individual counterexamples
Symmetric models:– general counter-examples
– indicvidual counterexamples
Positive: successes
– general successes
– general successes
– individual successes
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!
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
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
8
Dogmatic behaviorKuhn/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
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 scepticismeQ2: voorbij waarneembaar? Nee observational realisme
- instrumentalisme Ja: wetenschappelijk realisme - constructief empiricisme
Q3: voorbij referentie? Nee referentieel realisme entiteiten realisme
Ja: theorie-realismeQ4: ideale conceptualisering? Nee constructief realisme
Ja: essentialistisch realisme
10
Vier perspectieven voor theorie-realisme
ModusFocus
actueel nomisch
waarheids-waarde
standaard/traditioneel
Giere
waarheids-benadering
Peirce/Niiniluoto
Popper
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
12
Conclusies ICRvooruitblik: 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
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
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 HE, 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)}
15
ComparisonsNot: 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 (AB) 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
16
From the HD- to the HP-method of testing
Definition E is a d-/p-test implication of H iffE is an ‘observational’ d-/p-consequence of H
• Idealization: Hypothetico-Deductive (HD-)Methodaims 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
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 meansCarnapian: only inductive likelihoodsBayesian: only inductive priorsHintikkian: both
– which one, no fact of the matter
18
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 ICR ICR
probabilistic ICR/SiS to be done to be done
19
HD- and HP-testing and -evaluationConsequences Test results Separate
evaluationresults* &reports
Comparativeevaluationresults &reports
Deductive
H E
d-confirmationorfalsification
positiveornegatived-results
**d-results (not)favoring H2 to H1
(9 log.pos.kinds)
Probabilistic
p(E/H)>p(E)
p-confirmationorp-disconfirmation
positiveornegativep-results
**p-results (not)favoring H2 to H1
(25 lp kinds)
* positive/negative results: à la Laudan’s emp. successes/problems** E favors H2 (relative) to H1 iff p(E/H2) >p(E/H1)(d- and p-reading)
20
D-/P-Evaluation Matrix (Bx: deductive boxes, ICR/SiS)
+: d-/p-results favorable for H2 relative to H1
H1negatived-result
negativepp-result
neutralp-result
positivepp-result
positived-result
negatived-result
B4 0
B2
B1
negativepp-result 0 neutralp-result
B8
B5 0
B3
positivepp-result 0
H2
positived-result
B9
B7
B6 0
21
DN-/PN-predictions and -explanations: “H predicts/explains E, assuming C (=A&B&C)” • DN-idealization
H&C E
• PN-concretizationp(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)
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!?
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)}
24
ReferencesKuipers, 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.