Sandhiya Vijayabaskaran

The paper presents a computational model of visual and goal-vector signal integration in spatial navigation using reinforcement learning, showing that independent use and integration of signals are crucial for navigation in uncertain environments.

CoBeL-RL is a simulation framework for modeling complex behavior and learning in neuroscience, offering virtual environments and RL algorithms for efficient simulation and analysis.

This study shows that navigation tasks influence the type of spatial representations (egocentric or allocentric) that emerge in a deep reinforcement learning model.

This study develops a reinforcement learning model that learns context-dependent extinction behavior from raw visual inputs, showing that context dependence can emerge without explicit context representation.