Abstract
One challenge that has to be addressed by the fast and frugal heuristics program is how people manage to select, from the abundance of cues that exist in the environment, those to rely on when making decisions. We hypothesize that causal knowledge helps people target particular cues and estimate their validities. This hypothesis was tested in three experiments. Results show that when causal information about some cues was available (Experiment 1), participants preferred to search for these cues first and to base their decisions on them. When allowed to learn cue validities in addition to causal information (Experiment 2), participants also became more frugal (i.e., they searched fewer of the available cues), made more accurate decisions, and were more precise in estimating cue validities than was a control group that did not receive causal information. These results can be attributed to the causal relation between the cues and the criterion, rather than to greater saliency of the causal cues (Experiment 3). Overall, our results support the hypothesis that causal knowledge aids in the learning of cue validities and is treated as a meta-cue for identifying highly valid cues.
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Ahn, W., &Kalish, C. W. (2000). The role of mechanism beliefs in causal reasoning. In F. C. Keil & R. A. Wilson (Eds.),Explanation and cognition (pp. 199–225). Cambridge, MA: MIT Press.
Ahn, W., Kalish, C. W., Medin, D. L., &Gelman, S. A. (1995). The role of covariation versus mechanism information in causal attribution.Cognition,54, 299–352.
Alba, J. W., &Hasher, L. (1983). Is memory schematic? Psychological Bulletin,93, 203–231.
Alloy, L. B., &Tabachnik, N. (1984). Assessment of covariation by humans and animals: The joint influence of prior expectations and current situational information.Psychological Review,91, 112–149.
Baumgartner, H. (1995). On the utility of consumers’ theories in judgments of covariation.Journal of Consumer Research,21, 634–643.
Brehmer, B. (1973). Note on the relation between single-cue probability learning and multiple-cue probability learning.Organizational Behavior & Human Performance,9, 246–252.
Bröder, A. (2000). Assessing the empirical validity of the “take-the-best” heuristic as a model of human probabilistic inference.Journal of Experimental Psychology: Learning, Memory, & Cognition,26, 1332–1346.
Bröder, A. (2003). Decision making with the “adaptive toolbox”: Influence of environmental structure, intelligence, and working memory load.Journal of Experimental Psychology: Learning, Memory, & Cognition,29, 611–625.
Bröder, A., &Schiffer, S. (2003). Take the best versus simultaneous feature matching: Probabilistic inferences from memory and effects of representation format.Journal of Experimental Psychology: General,132, 277–293.
Broniarczyk, S. M., &Alba, J. W. (1994). Theory versus data in pre diction and correlation tasks.Organizational Behavior & Human Decision Processes,57, 117–139.
Bullock, M., Gelman, R., &Baillargeon, R. (1982). The development of causal reasoning. In W. J. Friedman (Ed.),The developmental psychology of time (pp. 209–254). New York: Academic Press.
Castellan, N. J. (1973). Multiple-cue probability learning with irrelevant cues.Organizational Behavior & Human Performance,9, 16–29.
Dieckmann, A., &Todd, P. M. (2004). Simple ways to construct search orders. In K. Forbus, D. Gentner, & T. Regier (Eds.),Proceedings of the 26th Annual Conference of the Cognitive Science Society (pp. 309–314). Mahwah, NJ: Erlbaum.
Edgell, S. E., &Hennessey, J. E. (1980). Irrelevant information and utilization of event base rates in nonmetric multiple-cue probability learning.Organizational Behavior & Human Performance,26, 1–6.
Eells, E. (1991).Probabilistic causality. Cambridge: Cambridge University Press.
Fugelsang, J. A., &Thompson, V. A. (2000). Strategy selection in causal reasoning: When beliefs and covariation collide.Canadian Journal of Experimental Psychology,54, 15–32.
Fugelsang, J. A., &Thompson, V. A. (2003). A dual-process model of belief and evidence interactions in causal reasoning.Memory & Cognition,31, 800–815.
Garcia-Retamero, R. (2007). The influence of knowledge about causal mechanisms on compound processing.Psychological Record,57, 295–306.
Garcia-Retamero, R., &Dieckmann, A. (2006). A critical view of the fast and frugal heuristics approach.Revista Latinoamericana de Psicología,38, 509–522.
Garcia-Retamero, R., &Hoffrage, U. (2006). How causal knowledge simplifies decision making.Minds & Machines,16, 365–380.
Garcia-Retamero, R., Hoffrage, U., &Dieckmann, A. (2007). When one cue is not enough: Combining fast and frugal heuristics with compound cue processing.Quarterly Journal of Experimental Psychology,60, 1197–1215.
Garcia-Retamero, R., Hoffrage, U., Dieckmann, A., &Ramos, M. (2007). Compound cue processing within the fast and frugal heuristic approach in non-linearly separable environments.Learning & Motivation,38, 16–34.
Garcia-Retamero, R., Takezawa, M., &Gigerenzer, G. (2006). How to learn good cue orders: When social learning benefits simple heuristics. In R. Sun & N. Miyake (Eds.), Proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 1352–1358). Mahwah, NJ: Erlbaum.
Gigerenzer, G., &Goldstein, D. G. (1996). Reasoning the fast and frugal way: Models of bounded rationality.Psychological Review,103, 650–669.
Gigerenzer, G., &Goldstein, D. G. (1999). Betting on one good reason: The take the best heuristic. In G. Gigerenzer, P. M. Todd, & the ABC Research Group,Simple heuristics that make us smart (pp. 75–95). New York: Oxford University Press.
Gigerenzer, G., Todd, P. M., &the ABC Research Group (1999).Simple heuristics that make us smart. New York: Oxford University Press.
Glymour, C., &Cheng, P. W. (1998). Causal mechanism and probability: A normative approach. In M. Oaksford & N. Chater (Eds.),Rational models of cognition (pp. 295–313). Oxford: Oxford University Press.
Gopnik, A., &Schulz, L. (2007).Causal learning: Psychology, philosophy, and computation. Oxford: Oxford University Press.
Juslin, P., &Persson, M. (2002). Probabilities from exemplars (PROBEX): A “lazy” algorithm for probabilistic inference from generic knowledge.Cognitive Science,26, 563–607.
Koslowski, B. (1996).Theory and evidence: The development of scientific reasoning. Cambridge, MA: MIT Press.
Koslowski, B., &Masnick, A. (2002). The development of causal reasoning. In U. Goswami (Ed.),Blackwell handbook of childhood cognitive development (pp. 257–281). Malden, MA: Blackwell.
Koslowski, B., &Okagaki, L. (1986). Non-Humean indices of causation in problem-solving situations: Causal mechanism, analogous effects, and the status of rival alternative accounts.Child Development,576, 1100–1108.
Koslowski, B., Okagaki, L., Lorenz, C., &Umbach, D. (1989). When covariation is not enough: The role of causal mechanism, sampling method, and sample size in causal reasoning.Child Development,60, 1316–1327.
Kruschke, J. K., &Johansen, M. K. (1999). A model of probabilistic category learning.Journal of Experimental Psychology: Learning, Memory, & Cognition,25, 1083–1119.
Medin, D. L. (1989). Concepts and conceptual structure.American Psychologist,44, 1469–1481.
Medin, D. L., Wattenmaker, W. D., &Hampson, S. E. (1987). Family resemblance, conceptual cohesiveness, and category construction.Cognitive Psychology,19, 242–279.
Murphy, G. L. (2002).The big book of concepts. Cambridge, MA: MIT Press.
Newell, B. R., Rakow, T., Weston, N. J., &Shanks, D. R. (2004). Search strategies in decision making: The success of “success.”Journal of Behavioral Decision Making,17, 117–137.
Newell, B. R., &Shanks, D. R. (2003). Take the best or look at the rest? Factors influencing “one-reason” decision making.Journal of Experimental Psychology: Learning, Memory, & Cognition,29, 53–65.
Newell, B. R., Weston, N. J., &Shanks, D. R. (2003). Empirical tests of a fast-and-frugal heuristic: Not everyone “takes-the-best.”Organizational Behavior & Human Decision Processes,91, 82–96.
Nisbett, R. E., &Ross, L. (1980).Human inference: Strategies and shortcomings of social judgments. Englewood Cliffs, NJ: Prentice-Hall.
Pearl, J. (2000).Causality. New York: Oxford University Press.
Reichenbach, H. (1956).The direction of time. Berkeley: University of California Press.
Schaller, M. (1992). In-group favoritism and statistical reasoning in social inference: Implications for formation and maintenance of group stereotypes.Journal of Personality & Social Psychology,63, 61–74.
Schaller, M., &O’Brien, M. (1992). Intuitive analysis of covariance and group stereotype formation.Personality & Social Psychology Bulletin,18, 776–785.
Shanks, D. R., Holyoak, K. J., &Medin, D. L. (1996).The psychology of learning and motivation (Vol. 34). San Diego: Academic Press.
Spellman, B. A., Price, C. M., &Logan, J. M. (2001). How two causes are different from one: The use of (un)conditional information in Simpson’s paradox.Memory & Cognition,29, 193–208.
Spirtes, P., Glymour, C., &Scheines, R. (1993).Causation, prediction, and search (Springer lecture notes in statistics). New York: Springer.
Spirtes, P., Glymour, C., &Scheines, R. (2000).Causation, prediction, and search (2nd ed.). Cambridge, MA: MIT Press.
Tenenbaum, J. B., Griffiths, T. L, & Niyogi, S. (in press). Intuitive theories as grammars for causal inference. In A. Gopnik & L. Schulz (Eds.),Causal learning: Psychology, philosophy, and computation. Oxford: Oxford University Press.
Todd, P. M., &Gigerenzer, G. (2000). Précis of simple heuristics that make us smart.Behavioral & Brain Sciences,23, 727–780.
Waldmann, M. R. (1996). Knowledge-based causal induction. In D. R. Shanks, K. J. Holyoak, & D. L. Medin (Eds.),The psychology of learning and motivation (Vol. 34, pp. 47–88). San Diego: Academic Press.
Waldmann, M. R., &Hagmayer, Y. (2001). Estimating causal strength: The role of structural knowledge and processing effort.Cognition,82, 27–58.
Waldmann, M. R., &Martignon, L. (1998). A Bayesian network model of causal learning. In M. A. Gernsbacher & S. J. Derry (Eds.),Proceedings of the 20th Annual Conference of the Cognitive Science Society (pp. 1102–1107). Mahwah, NJ: Erlbaum.
Wallin, A., &Gärdenfors, P. (2000). Smart people who make simple heuristics work.Behavioral & Brain Sciences,23, 765.
Wright, J. C., &Murphy, G. L. (1984). The utility of theories in intuitive statistics: The robustness of theory-based judgments.Journal of Experimental Psychology: General,113, 301–322.
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Garcia-Retamero, R., Wallin, A. & Dieckmann, A. Does causal knowledge help us be faster and more frugal in our decisions?. Memory & Cognition 35, 1399–1409 (2007). https://doi.org/10.3758/BF03193610
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DOI: https://doi.org/10.3758/BF03193610