Welcome to the reading group presentation!
In this presentation, Manisha will present a paper which explores how computational cognitive science helps us understand human decision-making using tools like probability theory, reinforcement learning, and statistical modeling. It reviews models that explain both how people make decisions (forward models) and how they reason about others’ decisions (inverse models). The authors highlight recent progress in integrating black-box learning with theory-driven approaches and reframe heuristics as rational strategies under cognitive constraints. The work bridges cognitive science with control and optimization perspectives.
Paper Link: Please find the relevant paper here.
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