Hlobil, Ulf (2016) Chains of Inferences and the New Paradigm in the Psychology of Reasoning. Review of Philosophy and Psychology, 7 (1). pp. 1-16.
Preview |
Text (application/pdf)
157kBHLOCOI.1.pdf - Accepted Version Available under License Spectrum Terms of Access. |
Official URL: http://dx.doi.org/10.1007/s13164-015-0230-y
Abstract
The new paradigm in the psychology of reasoning draws on Bayesian formal frameworks, and some advocates of the new paradigm think of these formal frameworks as providing a computational-level theory of rational human inference. I argue that Bayesian theories should not be seen as providing a computational-level theory of rational human inference, where by “Bayesian theories” I mean theories that claim that all rational credal states are probabilistically coherent and that rational adjustments of degrees of belief in the light of new evidence must be in accordance with some sort of conditionalization. The problems with the view I am criticizing can best be seen when we look at chains of inferences, rather than single-step inferences. Chains of inferences have been neglected almost entirely within the new paradigm.
Divisions: | Concordia University > Faculty of Arts and Science > Philosophy |
---|---|
Item Type: | Article |
Refereed: | Yes |
Authors: | Hlobil, Ulf |
Journal or Publication: | Review of Philosophy and Psychology |
Date: | March 2016 |
Digital Object Identifier (DOI): | 10.1007/s13164-015-0230-y |
Keywords: | Classical Logic; Human Reasoning; Credal State; Rational Inference; Rational Reasoning |
ID Code: | 983493 |
Deposited By: | ULF HLOBIL |
Deposited On: | 08 Feb 2018 14:31 |
Last Modified: | 08 Feb 2018 14:31 |
References:
Adams, E.W. 1998. A primer of probability logic. Stanford: CSLI Publications.Alchourrón, C.E., P. Gärdenfors, and D. Makinson. 1985. On the logic of theory change: partial meet contraction and revision functions. Journal of Symbolic Logic 50: 510–530.
Broome, J. 2013. Rationality through reasoning. Oxford: Wiley-Blackwell.
Chandler, J. 2014. Subjective probabilities need not be sharp. Erkenntnis: 1–14. doi: 10.1007/s10670-013-9597-2.
Chater, N., and M. Oaksford. 1999. The probability heuristics model of syllogistic reasoning. Cognitive Psychology 38: 191–258. doi: 10.1006/cogp.1998.0696.
Chater, N., and M. Oaksford. 2009. Local and global inferential relations: Response to Over (2009). Thinking and Reasoning 15: 439–446. doi: 10.1080/13546780903361765.
Cherubini, P., and P. Johnson-Laird. 2004. Does everyone love everyone? The psychology of iterative reasoning. Thinking and Reasoning 10: 31–53.
Elga, A. 2010. Subjective probabilities should be sharp. Philosophers’ Imprint 10.
Elqayam, S., and J.S.B.T. Evans. 2013. Rationality in the new paradigm: strict versus soft Bayesian approaches. Thinking and Reasoning 19: 453–470. doi: 10.1080/13546783.2013.834268.
Elqayam, S., and D.E. Over. 2012. Probabilities, beliefs, and dual processing: The paradigm shift in the psychology of reasoning. Mind & Society 11: 27–40. doi: 10.1007/s11299-012-0102-4.
Elqayam, S., and D.E. Over. 2013. New paradigm psychology of reasoning: An introduction to the special issue edited by Elqayam, Bonnefon, and Over. Thinking and Reasoning 19: 249–265. doi: 10.1080/13546783.2013.841591.
Evans, J.S.B.T. 2012. Questions and challenges for the new psychology of reasoning. Thinking and Reasoning 18: 5–31. doi: 10.1080/13546783.2011.637674
Gilio, A. 2012. Generalizing inference rules in a coherence-based probabilistic default reasoning. International Journal of Approximate Reasoning 53: 413–434. doi: 10.1016/j.ijar.2011.08.004.
Harman, G.H. 1986. Change in view: principles of reasoning. Cambridge: MIT Press.
Hedden, B. (forthcoming). Reasons without persons: rationality, identity, and time. Oxford: Oxford University Press.
Howson, C., and P. Urbach. 2006. Scientific reasoning: the Bayesian approach, 3rd ed. Chicago: Open Court Publishing.
Jago, M. 2009. Epistemic logic for rule-based agents. Journal of Logic, Language and Information 18: 131–158.
Jeffrey, R.C. 1970. Dracula meets Wolfman: Acceptance vs. partial belief. In Induction, acceptance, and rational belief, ed. M. Swain, 157–185. Dordrecht: Reidel.
Jones, M., and B.C. Love. 2011. Bayesian fundamentalism or enlightenment? On the explanatory status and theoretical contributions of Bayesian models of cognition. Behavioral and Brain Sciences 34: 169–188. doi: 10.1007/BF01454201.
Maher, P. 1993. Betting on theories. Cambridge: Cambridge University Press.
Moss, S. (forthcoming). Credal dilemmas. Noûs.
Oaksford, M., and N. Chater. 1994. A rational analysis of the selection task as optimal data selection. Psychological Review 101: 608–631.
Oaksford, M., and N. Chater. 1998. Rationality in an uncertain world: essays on the cognitive science of human reasoning. Hove: Psychology Press.
Oaksford, M., and N. Chater. 2001. The probabilistic approach to human reasoning. Trends in Cognitive Sciences 5: 349–357. doi: 10.1016/S1364-6613(00)01699-5.
Oaksford, M., and N. Chater. 2007. Bayesian rationality: the probabilistic approach to human reasoning. Oxford: Oxford University Press.
Oaksford, M., N. Chater, and J. Larkin. 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.
Pfeifer, N. 2013. The new psychology of reasoning: A mental probability logical perspective. Thinking and Reasoning 19: 329–345.
Pfeifer, N., and I. Douven. 2014. Formal epistemology and the new paradigm psychology of reasoning. Review of Philosophy and Psychology 5: 199–221. doi: 10.1007/s13164-013-0165-0.
Pfeifer, N., and G.D. Kleiter. 2006. Inference in conditional probability logic. Kybernetika42: 391–404
Pfeifer, N., and G.D. Kleiter. 2009. Framing human inference by coherence based probability logic. Journal of Applied Logic 7: 206–217. doi: 10.1016/j.jal.2007.11.005.
Simon, H.A. 1976. From substantive to procedural rationality. In Method and appraisal in economics, ed. S.J. Latsis, 129–148. Cambridge: Cambridge University Press.
Singmann, H., Klauer, K. C. & Over, D. E. 2014. New normative standards of conditional reasoning and the dual-source model. Frontiers in Psychology 5. doi: 10.3389/fpsyg.2014.00316.
Staffel, J. 2013. Can there be reasoning with degrees of belief? Synthese 190: 3535–3551. doi: 10.1007/s11229-012-0209-5.
Stenning, K., and M. van Lambalgen. 2009. “Nonmonotonic” does not mean “probabilistic”. Behavioral and Brain Sciences 32: 102–103. doi: 10.1017/S0140525X0900048X.
van der Henst, J.-B., Y. Yang, and P.N. Johnson-Laird. 2002. Strategies in sentential reasoning. Cognitive Science 26: 425–468.
Wedgwood, R. 2012. Outright belief. Dialectica 66: 309–329.
Repository Staff Only: item control page