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Systematic rationality norms provide research roadmaps and clarity

Published online by Cambridge University Press:  14 October 2011

Niki Pfeifer
Niki Pfeifer
Affiliation:
Ludwig-Maximilians-Universität München, Fakultät 10, Munich Center for Mathematical Philosophy, D-80539 München, Germany. [email protected]
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Abstract

Normative theories like probability logic provide roadmaps for psychological investigations. They make theorizing precise. Therefore, normative considerations should not be subtracted from psychological research. I explain why conditional elimination inferences involve at least two norm paradigms; why reporting agreement with rationality norms is informative; why alleged asymmetric relations between formal and psychological theories are symmetric; and I discuss the arbitration problem.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 34 , Issue 5 , October 2011 , pp. 263 - 264
Copyright
Copyright © Cambridge University Press 2011

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References

Coletti, G. & Scozzafava, R. (2002) Probabilistic logic in a coherent setting. Kluwer Academic.Google Scholar
Evans, J. St. B. T. (1982) The psychology of deductive reasoning. Routledge.Google Scholar
Ford, M. (2004) System LS: A three-tiered nonmonotonic reasoning system. Computational Intelligence 20(1):89–108.CrossRefGoogle Scholar
Ford, M. (2005) On using human nonmonotonic reasoning to inform artificial systems. Psychologica Belgica 45:57–70.CrossRefGoogle Scholar
Fugard, A. J. B., Pfeifer, N., Mayerhofer, B. & Kleiter, G. D. (2011b) How people interpret conditionals: Shifts towards the conditional event. Journal of Experimental Psychology: Learning, Memory, and Cognition 37(3):635–48.Google Scholar
Kraus, S., Lehmann, D. & Magidor, M. (1990) Nonmonotonic reasoning, preferential models and cumulative logics. Artificial Intelligence 44:167–207.Google Scholar
Pfeifer, N. & Kleiter, G. D. (2002) Experiments on nonmonotonic reasoning: The coherence of human probability judgments. In: Proceedings of the 1st Salzburg Workshop on Paradigms of Cognition, ed. Leitgeb, H. & Schurz, G.. Universität Salzburg, Institut für Philosophie. [Shortened version published in 2005 in Synthese 146(1–2):93–109.] Google Scholar
Pfeifer, N. & Kleiter, G. D. (2005) Towards a mental probability logic. Psychologica Belgica 45(1):71–99.CrossRefGoogle Scholar
Pfeifer, N. & Kleiter, G. D. (2006) Inference in conditional probability logic. Kybernetika 42:391–404.Google Scholar
Pfeifer, N. & Kleiter, G. D. (2009) Framing human inference by coherence based probability logic. Journal of Applied Logic 7(2):206–17.Google Scholar
Pfeifer, N. & Kleiter, G. D. (2010) The conditional in mental probability logic. In: Cognition and conditionals: Probability and logic in human thought, ed. Oaksford, M. & Chater, N., pp. 153–73. Oxford University Press.CrossRefGoogle Scholar
Pfeifer, N. & Kleiter, G. D. (2011) Uncertain deductive reasoning. In: The science of reason: A Festschrift for Jonathan St. B.T. Evans, ed. Manktelow, K. I., Over, D. E. & Elqayam, S., pp. 145–66. Psychology Press.Google Scholar