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We study the computational mechanisms by which humans adaptively encode and retrieve memories. The ultimate aim of this research is to leverage these theoretical insights to enhance human memory performance and design more effective artificial learning agents.
To move towards a generalized theory of memory, we build computational models that unify empirical findings across different tasks and bridge memory research conducted in well-controlled laboratory environments with studies in naturalistic settings.