Learning to Choose: Associative Learning and Preference Formation in Risky Choice
Conference paper
Kusev, P., van Schaik, P. and Love, B. (2017). Learning to Choose: Associative Learning and Preference Formation in Risky Choice. 58th Annual Meeting of the Psychonomic Society. Vancouver Canada 09 - 12 Nov 2017
Authors | Kusev, P., van Schaik, P. and Love, B. |
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Type | Conference paper |
Abstract | Theories of decision-making preferences and utility formation (e.g., normative, descriptive and experience- based) share common assumptions and predictions. Despite all their differences, normative (utilitarian), psychological descriptive and experience-based decision theories predict that human agents have stable and coherent preferences, informed by consistent use of psychological strategy/processing (computational or non-computational sampling) that guide their choices between alternatives varying in risk and reward. Rather than having fixed preferences/strategies (utilitarian or non-utilitarian) for risky choice, we argue that decision preferences are constructed dynamically based on strategy selection as a reinforcement-learning model. Accordingly, we found that associative learning (supervised learning tasks) predicts strategy selection (probability-bet and dollar-bet strategies) and govern decision makers’ risky preferences. |
Year | 2017 |
Web address (URL) | https://cdn.ymaws.com/www.psychonomic.org/resource/resmgr/annual_meeting/2017_meeting/2017_PS-Abstracts-v11-09.pdf |
Accepted author manuscript | License File Access Level Open |
Publication dates | |
09 Nov 2017 | |
Publication process dates | |
Accepted | 10 Aug 2017 |
Deposited | 02 Nov 2022 |
Web address (URL) of conference proceedings | https://cdn.ymaws.com/www.psychonomic.org/resource/resmgr/annual_meeting/2017_meeting/2017_PS-Abstracts-v11-09.pdf |
https://openresearch.lsbu.ac.uk/item/923q5
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