16:30 - 18:00
Mon-B22-Talk III-
Mon-Talk III-
Room: B22
Chair/s:
Thorsten Pachur, Chris Donkin
Computational modeling provides a powerful tool to study and measure the cognitive underpinnings of behavior. This symposium features recent advances in the application of computational modeling in experimental psychology, showcasing its immense value for learning about cognitive processing across a wide range of applications. Florian Bolenz presents an analysis with the computational framework of metareasoning to model differences between younger and older adults in boundedly rational strategy selection during risky choice. The contribution by Ann-Katrin Hosch features a new evidence-accumulation exemplar model of category learning that allows an examination of how the variance of sampled examplars influences categorization. Chris Donkin presents a project that uses computational modeling to distinguish basic memory processes and strategic response in the DRM paradigm, highlighting the often neglected role of reasoning processes in recognition memory research. Veronika Zilker integrates attentional processes in the computational modeling of decision making with cumulative prospect theory; specifically, she examines whether attentional processes might be key drivers of the description-experience gap in risky choice. In the contribution by David Izydorczyk, a blending model of exemplar-based and rule-based judgment is used to model the cognitive processes underlying quantitative judgment of complex stimuli. Benjamin Kowialiewski presents a connectionist model of visuospatial working memory to study the impact of visuospatial proximity on memory performance. The symposium will bring together researchers from various research groups in Europe, reflecting the increasing popularity of cognitive modeling in experimental psychology.
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Investigating Age Differences in Risky Choice through the Lens of a Rational Strategy Selection Model
Mon-B22-Talk III-01
Presented by: Florian Bolenz
Florian Bolenz 1, Thorsten Pachur 1, 2
1 Max Planck Institute for Human Development, 2 Technical University of Munich
How people make decisions under risk changes across the adult lifespan. Here, we investigate to what extent age differences in risky choice can be understood as reflecting differences in the rational selection of different decision strategies. For this purpose, we use a rational strategy-selection model that assumes that decision makers select decision strategies by optimizing the trade-off between a strategy's payoff and the cost of implementing this strategy. Analyzing risky choice data from 60 younger and 62 older adults, we find that the rational strategy-selection model is able to capture age differences with respect to decision quality and risk preference. According to the model, younger and older adults differ in their strategy use. However older adults do not use simpler strategies or weight strategy cost more strongly during strategy selection. Instead, older adults seem to rely more frequently on strategies that focus more strongly on information about outcomes than on information about probabilities for making a choice. Our results suggest that age differences in risky choice might not primarily be driven by cognitive factors but instead reflect experience-based or motivational differences in strategy use. More generally, our study highlights the usefulness of a strategy-selection perspective for understanding age-related differences in decision making and points to an alternative to more commonly used psychoeconomic modeling frameworks.
Keywords: aging, cognitive modeling, decision making, risk
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