Advertisement

Review of Philosophy and Psychology

, Volume 7, Issue 1, pp 1–16 | Cite as

Chains of Inferences and the New Paradigm in the Psychology of Reasoning

  • Ulf Hlobil
Article

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.

Keywords

Classical Logic Human Reasoning Credal State Rational Inference Rational Reasoning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

Thanks to Michael Caie, Adam Marushak, Robert Brandom, Karl Schafer and an anonymous referee for this journal for their insightful comments.

References

  1. Adams, E.W. 1998. A primer of probability logic. Stanford: CSLI Publications.Google Scholar
  2. 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.CrossRefGoogle Scholar
  3. Broome, J. 2013. Rationality through reasoning. Oxford: Wiley-Blackwell.CrossRefGoogle Scholar
  4. Chandler, J. 2014. Subjective probabilities need not be sharp. Erkenntnis: 1–14. doi:  10.1007/s10670-013-9597-2.
  5. Chater, N., and M. Oaksford. 1999. The probability heuristics model of syllogistic reasoning. Cognitive Psychology 38: 191–258. doi: 10.1006/cogp.1998.0696.CrossRefGoogle Scholar
  6. 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.CrossRefGoogle Scholar
  7. Cherubini, P., and P. Johnson-Laird. 2004. Does everyone love everyone? The psychology of iterative reasoning. Thinking and Reasoning 10: 31–53.CrossRefGoogle Scholar
  8. Elga, A. 2010. Subjective probabilities should be sharp. Philosophers’ Imprint 10.Google Scholar
  9. 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.CrossRefGoogle Scholar
  10. 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.CrossRefGoogle Scholar
  11. 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.CrossRefGoogle Scholar
  12. 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.CrossRefGoogle Scholar
  13. 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.CrossRefGoogle Scholar
  14. Harman, G.H. 1986. Change in view: principles of reasoning. Cambridge: MIT Press.Google Scholar
  15. Hedden, B. (forthcoming). Reasons without persons: rationality, identity, and time. Oxford: Oxford University Press.Google Scholar
  16. Howson, C., and P. Urbach. 2006. Scientific reasoning: the Bayesian approach, 3rd ed. Chicago: Open Court Publishing.Google Scholar
  17. Jago, M. 2009. Epistemic logic for rule-based agents. Journal of Logic, Language and Information 18: 131–158.CrossRefGoogle Scholar
  18. Jeffrey, R.C. 1970. Dracula meets Wolfman: Acceptance vs. partial belief. In Induction, acceptance, and rational belief, ed. M. Swain, 157–185. Dordrecht: Reidel.CrossRefGoogle Scholar
  19. 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.CrossRefGoogle Scholar
  20. Maher, P. 1993. Betting on theories. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  21. Moss, S. (forthcoming). Credal dilemmas. Noûs.Google Scholar
  22. Oaksford, M., and N. Chater. 1994. A rational analysis of the selection task as optimal data selection. Psychological Review 101: 608–631.CrossRefGoogle Scholar
  23. Oaksford, M., and N. Chater. 1998. Rationality in an uncertain world: essays on the cognitive science of human reasoning. Hove: Psychology Press.CrossRefGoogle Scholar
  24. 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.CrossRefGoogle Scholar
  25. Oaksford, M., and N. Chater. 2007. Bayesian rationality: the probabilistic approach to human reasoning. Oxford: Oxford University Press.CrossRefGoogle Scholar
  26. 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.Google Scholar
  27. Over, D.E. 2009. New paradigm psychology of reasoning. Thinking and Reasoning 15: 431–438.CrossRefGoogle Scholar
  28. Pfeifer, N. 2013. The new psychology of reasoning: A mental probability logical perspective. Thinking and Reasoning 19: 329–345.CrossRefGoogle Scholar
  29. 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.CrossRefGoogle Scholar
  30. Pfeifer, N., and G.D. Kleiter. 2006. Inference in conditional probability logic. Kybernetika 42: 391–404.Google Scholar
  31. 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.CrossRefGoogle Scholar
  32. 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.CrossRefGoogle Scholar
  33. 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.
  34. Staffel, J. 2013. Can there be reasoning with degrees of belief? Synthese 190: 3535–3551. doi: 10.1007/s11229-012-0209-5.CrossRefGoogle Scholar
  35. Stenning, K., and M. van Lambalgen. 2009. “Nonmonotonic” does not mean “probabilistic”. Behavioral and Brain Sciences 32: 102–103. doi: 10.1017/S0140525X0900048X.CrossRefGoogle Scholar
  36. van der Henst, J.-B., Y. Yang, and P.N. Johnson-Laird. 2002. Strategies in sentential reasoning. Cognitive Science 26: 425–468.CrossRefGoogle Scholar
  37. Wedgwood, R. 2012. Outright belief. Dialectica 66: 309–329.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Department of PhilosophyUniversity of PittsburghPittsburghUSA

Personalised recommendations