Information Processing in Repeated Monetary Gambles


We base our decisions on the available information. However, we do not give every piece of information the same weight, and we disregard some information depending on the type of decision and the circumstances. Applying modifications of classical monetary gambles, I investigate the information integration in fast and slow decisions on a behavioral level. Using cognitive modeling, I seek to understand and explain the underlying processes.  In the study of repeated monetary gambles, researchers typically look at predictions of different choice strategies or rules and compare how well they explain the overall choice behavior of participants. Choice proportions and response times are thereby considered as independent sources of information. However, if you take a closer look at what happens over the time course of a decision, conclusions sometimes change: In the gambles I am using, participants have to choose between two competing lotteries, of which one of them is designed to be the mathematically optimal choice in the long run. Participants strongly preferred the lotteries with a higher winning probability, as if they ignored potential rewards. Distributional analyses of response times revealed that this preference was particularly strong for fast responses. With increasing response time, participants integrated both pieces of information (i.e. winning probability and potential outcome), leading to both more and less optimal choices depending on the gamble.  Examining how different feedback types or presentation formats modulate choice behavior in the above mentioned gambles is one part of my current research. The most recent part of my thesis is testing the extent to which process models (e.g., diffusion models) can be used in order to complement such detailed perspective on choice behavior.

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Period: 01.01.2013 – 30.06.2017