Abstract
Reasoning is a core ability of humans being explored across disciplines during the last millenia. Investigations focused, however, often on identifying general principles of human reasoning or correct reasoning, but less on predicting conclusions for an individual reasoner. It is a desideratum to have artificial agents that can adapt to the individual human reasoner. We present an approach which successfully predicts individual performance across reasoning domains for reasoning about quantified or conditional statements using collaborative filtering techniques. Our proposed models are simple but efficient: they take some answers from a subject, and then build pair-wise similarities and predict missing answers based on what similar reasoners concluded. Our approach has a high accuracy in different data sets, and maintains this accuracy even when more than half of the data is missing. These features suggest that our approach is able to generalize and account for realistic scenarios, making it an adequate tool for artificial reasoning systems for predicting human inferences.
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Braine, M.D., O’Brien, D.P.: A theory of if: a lexical entry, reasoning program, and pragmatic principles. Psychol. Rev. 98(2), 182 (1991)
Chapman, L.J., Chapman, J.P.: Atmosphere effect re-examined. J. Exp. Psychol. 58(3), 220 (1959)
Cheng, P.W., Holyoak, K.J.: Pragmatic reasoning schemas. Cogn. Psychol. 17(4), 391–416 (1985)
Evans, J.S.B.T., Lynch, J.S.: Matching bias in the selection task. Br. J. Psychol. 64(3), 391–397 (1973)
Evans, J.S.B.T.: In two minds: dual-process accounts of reasoning. Trends Cogn. Sci. 7(10), 454–459 (2003)
Evans, J.S.B.T.: The heuristic-analytic theory of reasoning: extension and evaluation. Psychon. Bull. Rev. 13(3), 378–395 (2006)
Goldberg, D., Nichols, D., Oki, B.M., Terry, D.: Using collaborative filtering to weave an information tapestry. Commun. ACM 35(12), 61–70 (1992)
Johnson-Laird, P.N.: Models of deduction. In: Reasoning: Representation and Process in Children and Adults, pp. 7–54 (1975)
Johnson-Laird, P.N.: Mental Models: Towards a Cognitive Science of Language, Inference, and Consciousness, no. 6. Harvard University Press (1983)
Johnson-Laird, P.N., Legrenzi, P., Legrenzi, M.S.: Reasoning and a sense of reality. Br. J. Psychol. 63(3), 395–400 (1972)
Johnson-Laird, P.N.: Deductive Reasoning. Wiley Online Library (1991)
Khemlani, S., Johnson-Laird, P.N.: Theories of the syllogism: a meta-analysis. Psychol. Bull. 138(3), 427 (2012)
Manktelow, K.I., Evans, J.S.B.T.: Facilitation of reasoning by realism: effect or non-effect? Br. J. Psychol. 70(4), 477–488 (1979)
Oaksford, M., Chater, N.: A rational analysis of the selection task as optimal data selection. Psychol. Rev. 101(4), 608 (1994)
Oaksford, M., Chater, N.: Bayesian Rationality: The Probabilistic Approach to Human Reasoning. Oxford University Press, Oxford (2007)
Polk, T.A., Newell, A.: Deduction as verbal reasoning. Psychol. Rev. 102(3), 533 (1995)
Ragni, M., Kola, I., Johnson-Laird, P.N.: On selecting evidence to test hypotheses: a theory of selection tasks. Psychol. Bull. 144(8), 779 (2018)
Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: GroupLens: an open architecture for collaborative filtering of netnews. In: Proceedings of the 1994 ACM Conference on Computer Supported Cooperative Work, pp. 175–186. ACM (1994)
Resnick, P., Varian, H.R.: Recommender systems. Commun. ACM 40(3), 56–58 (1997)
Revlis, R.: Two models of syllogistic reasoning: feature selection and conversion. J. Verbal Learn. Verbal Behav. 14(2), 180–195 (1975)
Rips, L.J.: The Psychology of Proof: Deductive Reasoning in Human Thinking. MIT Press, Cambridge (1994)
Sarwar, B., Karypis, G., Konstan, J., Riedl, J.: Item-based collaborative filtering recommendation algorithms. In: Proceedings of the 10th International Conference on World Wide Web, pp. 285–295. ACM (2001)
Segaran, T.: Programming Collective Intelligence: Building Smart Web 2.0 Applications. O’Reilly Media, Inc., Sebastopol (2007)
Wason, P.C.: Reasoning. In: Foss, B. (ed.) New Horizons in Psychology (1966)
Wason, P.C., Shapiro, D.: Natural and contrived experience in a reasoning problem. Q. J. Exp. Psychol. 23(1), 63–71 (1971)
Wason, P.C., Johnson-Laird, P.N.: Psychology of Reasoning: Structure and Content, vol. 86. Harvard University Press (1972)
Acknowledgements
This research has been supported by a Heisenberg grant to MR (RA 1934/3-1 and RA 1934/4-1) and RA 1934/2-1. The authors would like to thank the anonymous reviewers for their valuable comments and suggestions.
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Kola, I., Ragni, M. (2018). Predict the Individual Reasoner: A New Approach. In: Trollmann, F., Turhan, AY. (eds) KI 2018: Advances in Artificial Intelligence. KI 2018. Lecture Notes in Computer Science(), vol 11117. Springer, Cham. https://doi.org/10.1007/978-3-030-00111-7_34
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DOI: https://doi.org/10.1007/978-3-030-00111-7_34
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