Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Minds and Machines
Erschienen in: Minds and Machines 1/2017

16.03.2017

Conditionals, Counterfactuals, and Rational Reasoning: An Experimental Study on Basic Principles

verfasst von: Niki Pfeifer, Leena Tulkki

Erschienen in: Minds and Machines | Ausgabe 1/2017

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

We present a unified approach for investigating rational reasoning about basic argument forms involving indicative conditionals, counterfactuals, and basic quantified statements within coherence-based probability logic. After introducing the rationality framework, we present an interactive view on the relation between normative and empirical work. Then, we report a new experiment which shows that people interpret indicative conditionals and counterfactuals by coherent conditional probability assertions and negate conditionals by negating their consequents. The data support the conditional probability interpretation of conditionals and the narrow-scope reading of the negation of conditionals. Finally, we argue that coherent conditional probabilities are important for probabilistic analyses of conditionals, nonmonotonic reasoning, quantified statements, and paradoxes.
Vorheriger Artikel Formal Nonmonotonic Theories and Properties of Human Defeasible Reasoning
Nächster Artikel Stability and Scepticism in the Modelling of Doxastic States: Probabilities and Plain Beliefs

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Anhänge
Nur mit Berechtigung zugänglich
Fußnoten
1
We thank Hans Rott for stimulating the construction of the rational monotonicity tasks.
 
Literatur
Adams, E. W. (1975). The logic of conditionals. An application of probability to deduction. Dordrecht: Reidel.MATH
Benferhat, S., Dubois, D., & Prade, H. (1997). Nonmonotonic reasoning, conditional objects and possibility theory. Artificial Intelligence, 92, 259–276.MathSciNetCrossRefMATH
Bezzazi, H., Makinson, D., & Pérez, R. P. (1997). Beyond rational monotony: Some strong non-horn rules for nonmonotonic inference relations. Journal of Logic and Computation, 7(5), 605–631.MathSciNetCrossRefMATH
Biazzo, V., & Gilio, A. (2000). A generalization of the fundamental theorem of de Finetti for imprecise conditional probability assessments. International Journal of Approximate Reasoning, 24(2–3), 251–272.MathSciNetCrossRefMATH
BonJour, L. (1985). The structure of empirical knowledge. Cambridge: Harvard University Press.
Bonnefon, J.-F., Da Silva Neves, R., Dubois, D., & Prade, H. (2012). Qualitative and quantitative conditions for the transitivity of perceived causation: Theoretical and experimental results. Annals of Mathematics and Artificial Intelligence, 64, 311–333.MathSciNetCrossRefMATH
Capotorti, A., Lad, F., & Sanfilippo, G. (2007). Reassessing accuracy rates of median decisions. American Statistician, 61(2), 132–138.MathSciNetCrossRef
Chater, N., & Oaksford, M. (1999). The probability heuristics model of syllogistic reasoning. Cognitive Psychology, 38, 191–258.CrossRef
Cohen, A. (1999). Generics, frequency adverbs, and probability. Linguistics and Philosophy, 22, 221–253.CrossRef
Cohen, A. (2012). Generics as modals. Recherches linguistiques de Vincennes, 41, 63–82.CrossRef
Coletti, G., & Scozzafava, R. (2002). Probabilistic logic in a coherent setting. Dordrecht: Kluwer.CrossRefMATH
Coletti, G., Scozzafava, R., & Vantaggi, B. (2015). Possibilistic and probabilistic logic under coherence: Default reasoning and System P. Mathematica Slovaca, 65(4), 863–890.MathSciNetCrossRefMATH
Cruz, N., Baratgin, J., Oaksford, M., & Over, D. E. (2015). Bayesian reasoning with ifs and ands and ors. Frontiers in Psychology, 6, Article 192.
Cruz, N., Baratgin, J., Oaksford, M., & Over, D. E. (2016). Centering and the meaning of conditionals. In A. Papafragou, D. Grodner, D. Mirman & J. Trueswell (Eds.), Proceedings of the 38th Annual Meeting of the Cognitive Science Society (pp. 1104–1109). Philadelphia, PA: The Cognitive Science Society.
Da Silva Neves, R., Bonnefon, J.-F., & Raufaste, E. (2002). An empirical test of patterns for nonmonotonic inference. Annals of Mathematics and Artificial Intelligence, 34, 107–130.MathSciNetCrossRefMATH
de Finetti, B. (1931/1993). On the subjective meaning of probability (translation; original work published in Fundamenta Mathematicae, 17, 1931). In P. Monari & D. Cocchi (Eds.), Probabilità e induzione (pp. 291–321). Bolognia: Cooperativa Libraria Universitaria Editrice Bologna.
de Finetti, B. (1937/1980). Foresight: Its logical laws, its subjective sources. In H. J. Kyburg & H. E. Smokler (Eds.), Studies in subjective probability (pp. 55–118). Huntington, New York: Robert E. Krieger Publishing Company.
de Finetti, B. (1970/1974). Theory of probability (Vols. 1, 2). Chichester: Wiley.
Douven, I. (2016). The epistemology of indicative conditionals: Formal and empirical approaches. Cambridge: Cambridge University Press.CrossRef
Elqayam, S., Bonnefon, J.-F., & Over, D. E. (Eds.). (2016). New paradigm psychology of reasoning: Basic and applied perspectives. London: Routledge.
Elqayam, S., & Evans, J. S. B. T. (2011). Substracting “ought” from “is”: Descriptivism versus normativism in the study of human thinking. Behavioral and Brain Sciences, 34, 233–290.CrossRef
Evans, J. S. B. T. (2012). Questions and challenges to the new psychology of reasoning. Thinking & Reasoning, 18(1), 5–31.CrossRef
Evans, J. S. B. T., Newstead, S. E., & Byrne, R. M. J. (1993). Human reasoning. The psychology of deduction. Hove: Lawrence Erlbaum.
Evans, J. S. B. T., & Over, D. E. (2004). If. Oxford: Oxford University Press.CrossRef
Evans, J. S. B. T., Thompson, V. A., & Over, D. E. (2015). Uncertain deduction and conditional reasoning. Frontiers in Psychology, 6, Article 398.
Ford, M. (2004). System LS: A three-tiered nonmonotonic reasoning system. Computational Intelligence, 20(1), 89–108.MathSciNetCrossRef
Fugard, A. J. B., Pfeifer, N., Mayerhofer, B., & Kleiter, G. D. (2011). How people interpret conditionals: Shifts towards the conditional event. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37(3), 635–648.
Gilio, A. (2002). Probabilistic reasoning under coherence in System P. Annals of Mathematics and Artificial Intelligence, 34, 5–34.MathSciNetCrossRefMATH
Gilio, A. (2012). Generalizing inference rules in a coherence-based probabilistic default reasoning. International Journal of Approximate Reasoning, 53(3), 413–434.MathSciNetCrossRefMATH
Gilio, A., Over, D. E., Pfeifer, N., & Sanfilippo, G. (2017). Centering and compound conditionals under coherence. In M. B. Ferraro (Ed.), Soft methods for data science (pp. 253–260). Berlin: Springer.CrossRef
Gilio, A., Pfeifer, N., & Sanfilippo, G. (2015). Transitive reasoning with imprecise probabilities. In S. Destercke & T. Denoeux (Eds.), Symbolic and quantitative approaches to reasoning with uncertainty (ECSQARU 2015) (pp. 95–105). Dordrecht: Springer LNAI 9161.
Gilio, A., Pfeifer, N., & Sanfilippo, G. (2016). Transitivity in coherence-based probability logic. Journal of Applied Logic, 14, 46–64.MathSciNetCrossRefMATH
Gilio, A., & Sanfilippo, G. (2011). Coherent conditional probabilities and proper scoring rules. In F. Coolen, G. De Cooman, T. Fetz & M. Oberguggenberger (Eds.), Proceedings of the 7th international symposium on imprecise probability: Theories and applications (pp. 189–198). Innsbruck: SIPTA.
Gilio, A., & Sanfilippo, G. (2013a). Conditional random quantities and iterated conditioning in the setting of coherence. In L. C. van der Gaag (Ed.), ECSQARU 2013 (Vol. 7958, pp. 218–229). Berlin: Springer.
Gilio, A., & Sanfilippo, G. (2013b). Conjunction, disjunction and iterated conditioning of conditional events. In R. Kruse, B. M. R, C. Moewes, M. A. Gil, P. Grzegorzewski, & O. Hryniewicz (Eds.), Synergies of soft computing and statistics for intelligent data analysis (pp. 399–407). Berlin: Springer.
Gilio, A., & Sanfilippo, G. (2013c). Probabilistic entailment in the setting of coherence: The role of quasi conjunction and inclusion relation. International Journal of Approximate Reasoning, 54(4), 513–525.MathSciNetCrossRefMATH
Gilio, A., & Sanfilippo, G. (2014). Conditional random quantities and compounds of conditionals. Studia Logica, 102(4), 709–729.MathSciNetCrossRefMATH
Grice, H. P. (1975). Logic and conversation. In P. Cole & J. L. Morgan (Eds.), Syntax and semantics (Vol. 3: Speech acts). New York: Seminar Press.
Johnson-Laird, P. N., & Tagart, J. (1969). How implication is understood. The American Journal of Psychology, 82(3), 367–373.CrossRef
Khemlani, S., & Johnson-Laird, P. N. (2012). Theories of the syllogisms: A meta-analysis. Psychological Bulletin, 138(3), 427–457.CrossRef
Kraus, S., Lehmann, D., & Magidor, M. (1990). Nonmonotonic reasoning, preferential models and cumulative logics. Artificial Intelligence, 44, 167–207.MathSciNetCrossRefMATH
Lad, F. (1996). Operational subjective statistical methods: A mathematical, philosophical, and historical introduction. New York: Wiley.MATH
Lehtinen, T. (1983). Suomen konditionaalin morfologisesta ja semanttisesta motivaatiosta. Virittäjä, 87, 482–507.
Lewis, D. (1973). Counterfactuals. Oxford: Blackwell.MATH
Lindworsky, J. (1916). Das schlußfolgernde Denken. Experimentellpsychologische Untersuchungen. Freiburg im Breisgau: Herdersche Verlagshandlung.
Macnamara, J. (1986). A border dispute. The place of logic in psychology. Cambridge: MIT Press.
Marr, D. (1982). Vision. A computational investigation into the human representation and processing of visual information. San Francisco: W. H. Freeman.
Mele, A., & Rawling, P. (Eds.). (2004). The Oxford handbook of rationality. New York: Oxford University Press.
Milne, P. (2012). Indicative conditionals, conditional probabilities, and the “defective truth-table”: A request for more experiments. Thinking & Reasoning, 18(2), 196–224.CrossRef
Nickerson, R. S. (Ed.). (2008). Aspects of rationality. Reflections on what it means to be rational and whether we are. New York: Psychology Press.
Oaksford, M., & Chater, N. (1994). A rational analysis of the selection task as optimal data selection. Psychological Review, 101, 608–631.CrossRef
Oaksford, M., & Chater, N. (2007). Bayesian rationality: The probabilistic approach to human reasoning. Oxford: Oxford University Press.CrossRef
Oaksford, M., & Chater, N. (2009). Précis of “Bayesian rationality: The probabilistic approach to human reasoning”. Behavioral and Brain Sciences, 32, 69–120.CrossRef
Oaksford, M., Chater, N., & Larkin, J. (2000). Probabilities and polarity biases in conditional inference. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 883–899.
Over, D. E. (2009). New paradigm psychology of reasoning. Thinking and Reasoning, 15, 431–438.CrossRef
Over, D. E., & Baratgin, J. (2017). The “defective” truth table: Its past, present, and future. In N. Galbraith, E. Lucas, & D. E. Over (Eds.), The thinking mind: A Festschrift for Ken Manktelow (pp. 15–28). Hove: Psychology Press.
Over, D. E., Hadjichristidis, C., Evans, J. S. B. T., Handley, S. J., & Sloman, S. (2007). The probability of causal conditionals. Cognitive Psychology, 54, 62–97.CrossRef
Pfeifer, N. (2006). Contemporary syllogistics: Comparative and quantitative syllogisms. In G. Kreuzbauer & G. J. W. Dorn (Eds.), Argumentation in Theorie und Praxis: Philosophie und Didaktik des Argumentierens (pp. 57–71). Wien: Lit Verlag.
Pfeifer, N. (2008). A probability logical interpretation of fallacies. In G. Kreuzbauer, N. Gratzl, & E. Hiebl (Eds.), Rhetorische Wissenschaft: Rede und Argumentation in Theorie und Praxis (pp. 225–244). Wien: Lit Verlag.  
Pfeifer, N. (2011). Systematic rationality norms provide research roadmaps and clarity. Commentary on Elqayam & Evans: Subtracting “ought” from “is”: Descriptivism versus normativism in the study of human thinking. Behavioral and Brain Sciences, 34, 263–264.CrossRef
Pfeifer, N. (2012). Experiments on Aristotle’s Thesis: Towards an experimental philosophy of conditionals. The Monist, 95(2), 223–240.CrossRef
Pfeifer, N. (2013a). The new psychology of reasoning: A mental probability logical perspective. Thinking & Reasoning, 19(3–4), 329–345.CrossRef
Pfeifer, N. (2013b). On argument strength. In F. Zenker (Ed.), Bayesian argumentation. The practical side of probability (pp. 185–193). Dordrecht: Synthese Library (Springer).
Pfeifer, N. (2016). Experimental probabilistic pragmatics beyond Bayes’ theorem. Zeitschrift für Sprachwissenschaft, 35(1), 89–96.CrossRef
Pfeifer, N., & Douven, I. (2014). Formal epistemology and the new paradigm psychology of reasoning. The Review of Philosophy and Psychology, 5(2), 199–221.CrossRef
Pfeifer, N., & Kleiter, G. D. (2003). Nonmonotonicity and human probabilistic reasoning. In Proceedings of the 6th workshop on uncertainty processing (pp. 221–234). Hejnice: September 24–27, 2003.
Pfeifer, N., & Kleiter, G. D. (2005b). Towards a mental probability logic. Psychologica Belgica, 45(1), 71–99.CrossRef
Pfeifer, N., & Kleiter, G. D. (2006a). Inference in conditional probability logic. Kybernetika, 42, 391–404.MathSciNetMATH
Pfeifer, N., & Kleiter, G. D. (2006b). Is human reasoning about nonmonotonic conditionals probabilistically coherent? In Proceedings of the 7th workshop on uncertainty processing (pp. 138–150). Mikulov: September 16–20, 2006.
Pfeifer, N., & Kleiter, G. D. (2007). Human reasoning with imprecise probabilities: Modus ponens and Denying the antecedent. In G. De Cooman, J. Vejnarová & M. Zaffalon (Eds.), Proceedings of the 5th international symposium on imprecise probability: Theories and applications (pp. 347–356). Prague: SIPTA.
Pfeifer, N., & Kleiter, G. D. (2009a). Framing human inference by coherence based probability logic. Journal of Applied Logic, 7(2), 206–217.MathSciNetCrossRefMATH
Pfeifer, N., & Kleiter, G. D. (2009b). Mental probability logic. Commentary on Oaksford & Chater: Bayesian rationality. Behavioral and Brain Sciences, 32, 98–99.CrossRef
Pfeifer, N., & Kleiter, G. D. (2010). The conditional in mental probability logic. In M. Oaksford & N. Chater (Eds.), Cognition and conditionals: Probability and logic in human thought (pp. 153–173). Oxford: Oxford University Press.  
Pfeifer, N., & Kleiter, G. D. (2011). Uncertain deductive reasoning. In K. Manktelow, D. E. Over, & S. Elqayam (Eds.), The science of reason: A Festschrift for Jonathan St. B.T. Evans (pp. 145–166). Hove: Psychology Press.
Pfeifer, N., & Sanfilippo, G. (2017). Square of opposition under coherence. In M. B. Ferraro (Ed.), Soft methods for data science (pp. 407–414). Berlin: Springer.
Pfeifer, N., & Stöckle-Schobel, R. (2015). Uncertain conditionals and counterfactuals in (non-)causal settings. In G. Arienti, B. G. Bara & S. G. (Eds.), Proceedings of the EuroAsianPacific joint conference on cognitive science (4th European conference on cognitive science; 10th International conference on cognitive science) (Vol. 1419, pp. 651–656). Aachen: CEUR Workshop Proceedings. Retrieved from http://​ceur-ws.​org/​Vol-1419/​paper0108.
Politzer, G., & Baratgin, J. (2015). Deductive schemas with uncertain premises using qualitative probability expressions. Thinking & Reasoning, 22(1), 78–98.CrossRef
Quine, W. O. (1950). Methods of logic. New York: Holt.MATH
Ramsey, F. P. (1929/1994). General propositions and causality (1929). In D. H. Mellor (Ed.), Philosophical papers by F. P. Ramsey (pp. 145–163). Cambridge: Cambridge University Press.
Rott, H. (2014). Unvergleichbarkeit und unabhängige Bedeutung. Zeitschrift für philosophische Forschung, 68, 237–250.CrossRef
Schurz, G. (2005). Non-monotonic reasoning from an evolution-theoretic perspective: Ontic, logical and cognitive foundations. Synthese, 1–2, 37–51.MathSciNetCrossRefMATH
Schurz, G., & Thorn, P. D. (2012). Reward versus risk in uncertain inference: Theorems and simulations. The Review of Symbolic Logic, 5(4), 574–612.MathSciNetCrossRefMATH
Stanovich, K. E. (1999). Who is rational. Studies of individual differences in reasoning. Mahwah: Erlbaum.
Stanovich, K. E., & West, R. F. (2000). Individual differences in reasoning: Implications for the rationality debate? Behavioral and Brain Sciences, 23, 645–726.CrossRef
Störring, G. (1908). Experimentelle Untersuchungen zu einfachen Schlußprozessen. Archiv für die Gesamte Psychologie, 11, 1–127.
Walley, P. (1991). Statistical reasoning with imprecise probabilities. London: Chapman and Hall.CrossRefMATH
Wallmann, C., & Kleiter, G. (2014). Degradation in probability logic: When more information leads to less precise conclusions. Kybernetika, 50(2), 268–283.MathSciNetMATH
Wason, P. C. (1966). Reasoning. In B. M. Foss (Ed.), New horizons in psychology I (pp. 106–137). Harmandsworth: Penguin.
Wason, P. C., & Johnson-Laird, P. N. (1972). The psychology of reasoning: Structure and content. Cambridge: Harvard University Press.
Metadaten
Titel
Conditionals, Counterfactuals, and Rational Reasoning: An Experimental Study on Basic Principles
verfasst von
Niki Pfeifer
Leena Tulkki
Publikationsdatum
16.03.2017
Verlag
Springer Netherlands
Erschienen in
Minds and Machines / Ausgabe 1/2017
Print ISSN: 0924-6495
Elektronische ISSN: 1572-8641
DOI
https://doi.org/10.1007/s11023-017-9425-6

Weitere Artikel der Ausgabe 1/2017

Minds and Machines 1/2017 Zur Ausgabe

OriginalPaper

The Strength of Desires: A Logical Approach

EditorialNotes

Data Philanthropy and Individual Rights

Book Review

Rafael Capurro, Michael Eldred and Daniel Nagel: Digital Whoness: Identity, Privacy and Freedom in the Cyberworld

EditorialNotes

Reasoning with Imperfect Information and Knowledge

OriginalPaper

Illusions in Reasoning

OriginalPaper

Formal Nonmonotonic Theories and Properties of Human Defeasible Reasoning

Premium Partner

    Bildnachweise