Rapid spatial learning via efficient exploration and inference
Nada Abdelrahman, Wanchen Jiang, Joshua Dudman, Ann Hermundstad · COSYNE 2025
Animals quickly learn to navigate to rewarding or salient landmarks in their environments. However, existing models often require thousands of trials to learn contingencies that animals learn within tens of trials, and they do so via unstructured sequences of actions that do not mimic real behavior. In this work, we study rapid learning in a hidden-target foraging task for mice in which animals learn to intercept an uncued target location within an open arena. To study the computational underpinnings of this learning, we build an agent that controls its speed and heading over time via a pre-sp
ePoster · Neuroscience