Tag Archives: Marewski

Single Strategy Framework and the Process of Changing Weights


cloudindexThis post starts from the conclusion of the previous post that the evidence supports a single strategy framework, looks at Julian Marewski’s criticism, and then piles on with ideas on how weights can be changed in a single strategy framework.

Marewski provided a paper for the special issue of the Journal of Applied Research in Memory and Cognition (2015)  on “Modeling and Aiding Intuition in Organizational Decision Making”:  “Unveiling the Lady in Black: Modeling and Aiding Intuition,” authored by Ulrich Hoffrage and Julian N. Marewski. The paper gives the parallel constraint satisfaction model a not so subtle knock:

By exaggerating and simplifying features or traits, caricatures can aid perceiving the real thing. In reality, both magic costumes and chastity belts are degrees on a continuum. In fact, many theories are neither solely formal or verbal. Glöckner and Betsch’s connectionist model of intuitive decision making, for instance, explicitly rests on both math and verbal assumptions. Indeed, on its own, theorizing at formal or informal levels is neither “good” nor “bad”. Clearly, both levels of description have their own merits and, actually, also their own problems. Both can be interesting, informative, and insightful – like the work presented in the first three papers of this special issue, which we hope you enjoy as much as we do. And both can border re-description and tautology. This can happen when a theory does not attempt to model processes. Examples are mathematical equations with free parameters that carry no explanatory value, but that are given quasi-psychological, marketable labels (e.g., “risk aversion”).

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Strategy Selection — Single or Multiple?

spannerindexThis post tries to do a little tying together on a familiar subject. I look at a couple of papers that provide more perspective than typical research papers provide. First is the preliminary dissertation of Anke Söllner. She provides some educated synthesis which my posts need, but rarely get. Two of her papers which are also part of her dissertation are discussed in the posts Automatic Decision Making and Tool Box or Swiss Army Knife? I also look at a planned special issue of the Journal of Behavioral Decision Making to address “Strategy Selection: A Theoretical and Methodological Challenge.”

Söllner’s work is concerned with the question:  which framework–multiple strategy or single strategy– describes multi-attribute decision making best? In multi-attribute decision making we have to choose among two or more options. Cues can be consulted and each cue has some validity in reference to the decision criterion. If the criterion is an objective one (e.g., the quantity of oil), the task is referred to as probabilistic inference, whereas a subjective criterion (e.g., preference for a day trip) characterizes a preferential choice task. The multiple strategy framework is most notably the adaptive toolbox that includes fast and frugal heuristics as individual strategies. Single strategy frameworks assume that instead of selecting one from several distinct decision strategies, decision makers employ the same uniform decision making mechanism in every situation. The single strategy frameworks include the evidence accumulation model and the connectionist parallel constraint satisfaction model.

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Cognitive Niches

vineyards-along-lake-genevaThis post is based on the 2011 paper by Julian Marewski and Lael Schooler published in the Psychological Review, “Cognitive Niches: An Ecological Model of Strategy Selection.” How do people select among different strategies to accomplish a given task?  By using ACT-R along with heuristic decision strategies, the authors can create a more general  bidirectional model that seems to be competitive with such models as parallel constraint satisfaction.  In 14 simulations and 10 experiments, they consider the choice between strategies that operate on the accessibility of memories and those that depend on elaborate knowledge about the world. Based on Internet statistics, their model quantitatively predicts people’s familiarity with and knowledge of real-world objects, the distributional characteristics of the associated speed of memory retrieval, and the cognitive niches of classic decision strategies, including those of the fluency, recognition, integration, lexicographic, and sequential-sampling heuristics.

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