Reinforcement Learning: Developing a Computational Metric for Assessing Reward Values
Abstract
This project presents a validated computational approach, using a specialized reinforcement learning (kRL) paradigm and computational modeling, for measuring computationally inferred reward values (cRVs) from participants' choices. The paradigm is adaptable for measuring the reward value of different types of visual stimuli and holds promise for studying motivation across a wide range of fields. If you're interested in applying this paradigm to your own work, we'd love to hear from you. Task materials and code are available upon request.
Fields of Study & Subjects
Neural and Behavioral Psychology Studies
Decision-Making and Behavioral Economics
Neurotransmitter Receptor Influence on Behavior
Publication details
- Journal / source
- OSF Preprints (OSF Preprints)
- Publication date
- 10 March 2026
- Language
- EN
- Document type
- Preprint