IngentaConnect Convergence and Constraints Revealed in a Qualitative Model Compa...

Authors: Lebiere, Christian; Gonzalez, Cleotilde; Warwick, Walter

Source: Journal of Cognitive Engineering and Decision Making, Volume 3, Number 2, Summer 2009 , pp. 131-155(25)

Publisher: Human Factors and Ergonomics Society

Abstract:

We contrasted and compared independently developed computational models of human performance in a common dynamic decision-making task. The task, called dynamic stocks and flows, is simple and tractable enough for laboratory experiments yet exhibits many characteristics of macrocognition. A macrocognitive model was developed using a computational instantiation of recognition-primed decision making. A microcognitive model was developed using the Adaptive Control of Thought - Rational (ACT-R) cognitive architecture. Both models followed an instance-based learning paradigm and displayed striking similarities, including their constraints, limitations, and the key breakthrough that enabled satisfactory (though still short of human-like) performance, suggesting the emergence of a general design pattern. On the basis of this comparison we argue that although some substantive differences remain, microcognitive and macrocognitive approaches provide complementary rather than contradictory accounts of human behavior.

Keywords: MACROCOGNITION; DYNAMIC DECISION MAKING; ACT-R; RECOGNITION-PRIMED DECISION MAKING; MODEL COMPARISON

Document Type: Research article

DOI: 10.1518/155534309X441880

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Convergence and Constraints Revealed in a Qualitative Model Comparison