Monthly Archives: March 2014

Take the Best

barkleydownloadThe Take the Best heuristic probably deserves its own post and this is it.  This post is based on the paper, “Evaluating the Coherence of Take-the-Best in Structured Environments,” written by Michael D. Lee and Shunan Zhang that appeared in the July 2012 Judgment and Decision Making. Heuristic decision-making models, like Take-the-best, rely on environmental regularities. They conduct a limited search, and ignore available information, by assuming there is structure in the decision making environment. Take-the best relies on at least two regularities: diminishing returns, which says that information found earlier in search is more important than information found later; and correlated information, which says that information found early in search is predictive of information found later.  Lee and Zhang develop new approaches to determining search orders, and to measuring cue discriminability, that make the reliance of Take-the-best on these regularities clear.

Lee and Zhang begin with a story about the 1992 Olympics. It was the first time professionals from the US NBA league were allowed to play in the men’s basketball competition. The US “Dream Team”, filled with stars like Michael Jordan, Magic Johnson, Larry Bird, Charles Barkley and Patrick Ewing, was one of the most dominant teams ever assembled for any sporting
competition. Their closest game was a 117–85 victory in the final over Croatia, and head coach Chuck Daly never felt the need to call a timeout during the tournament. Making predictions about the outcomes of sporting contests is notoriously difficult, but the Dream Team made some predictions easy. Imagine trying to predict whether or not the US would beat its first opponent in the tournament, Angola, and examining the players in each team, beginning with the starting five, and moving to the bench players. At some point early in the US list—maybe
after Jordan, Johnson, Bird, Barkley and Ewing—there would be no need to look further. No matter who else was on the US roster, or the Angolan roster, the outcome is already clear. The Dream Team also made predictions easy during the course of games. Such decisions about a US victory are noncompensatory, because not all of the available information is used, and so the ignored information cannot compensate for—that is, change the decision based on—the
information that is used. The remaining player rosters are not examined, and the rest of the game is not watched.

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Evidence Accumulation Model

evidencedownloadMy first notice of this model was in the Sollner et al paper. My quick search finds that this 2004 paper, “Evidence accumulation in decision making:  Unifying the “take the best” and the “rational” models,” by Michael D. Lee and Tarrant Cummins  is the sole exposition of the model.

A simple but common type of decision requires choosing which of two alternatives has the greater (or the lesser) value on some variable of interest. Examples of these forced-choice decisions range from the everyday (e.g., deciding whether a red or a green curry will taste
better for lunch), to the moderately important (e.g., deciding whether Madrid or Rome will provide the more enjoyable holiday), to the very important (e.g., deciding whether cutting the red or the black wire is more likely to lead to the destruction of the world).

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Swiss Army Knife or Adaptive Tool Box?

giant-swiss-army-knife-3This post is based on the paper: “Single-process versus multiple-strategy models of decision making: Evidence from an information intrusion paradigm,” written by Anke Söllner,  Arndt Bröder,  Andreas Glöckner, and Tilmann Betsch. It appeared in Acta Psychologica in January 2014. It is a well done overview of multi-attribute decision models (Multi-attribute decision making deals with preferential choice e.g., “Which dessert do you like better?” and probabilistic inferences e.g., “Which dessert contains more calories?”),  along with clever experiments.  I am confused that it is single process vs multiple strategy. I would think that it would be process vs. process or strategy vs strategy.

This appears to me to be another polite skirmish in the continuing battle between fast and frugal heuristics and compensatory connectionist models. Do we change strategies or adjust decision thresholds or weights? However, the researchers have moved back to broader frameworks to get a different way to study and attack.  This paper has an interesting group of authors. Sollner and Broder wrote a paper last year that looked at similar issues, but focused on the importance of looking separately at how information is acquired and how information is integrated.  Glockner and Betsch are prime proponents of parallel constraint satisfaction theory– a single process model that apparently is weak on information acquisition. I will expect a Gigerenzer  or Marewski counter move soon for the fast and frugal heuristics side. I should note that there seems to be much respect between those with differing views, and the idea that probably everyone is a little bit wrong and a little bit right seems to pervade.

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Transitivity

intransitiveimagesThis post is based on a paper that does a good job of providing a general picture of some of the big questions in decision making.  The experiments with their small samples (even though the results are statistically significant) seem unlikely to be definitive, but the overall measure of transitivity, I think is a good one.  I usually think about transitivity only once a year, when I am getting my eyes tested–Which one is clearer is it a or b? Now is it b or c? …Transitivity is usually considered required for rationality. In this paper, they use it as a measure of both intuition and analysis. Of course, transitivity does not work in rock, paper, scissors, and humans seem to be able to be quite irrational in certain of their preferences.

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