Agency rescues competition for credit assignment among predictive cues from adverse learning conditions
M. Kang, I. Reverte, S. G. Volz, K. Kaufman, S. Fevola, A. Matarazzo, F. H. Alhazmi, I. Marquez, M. D. Iordanova, G. R. Esber
Abstract
A fundamental assumption of learning theories is that the credit assigned to predictive cues is not simply determined by their probability of reinforcement, but by their ability to compete with other cues present during learning. This assumption has guided behavioral and neural science research for decades, and tremendous empirical and theoretical advances have been made identifying the mechanisms of cue competition. However, when learning conditions are not optimal (e.g., when training is massed), credit assignment is no longer competitive. This is a catastrophic failure of the learning system that exposes the individuals vulnerability to form spurious associations in the real world. Here, we uncover that cue competition can be rescued when conditions are suboptimal provided that the individual has agency over the learning experience. Our findings reveal a new connection between agency over learning and credit assignment to cues, and open new avenues of investigation into the underlying mechanisms.
02 /Specification & Classification
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