5 citations · 5 across the 2 of their papers we have counts for
2 papers
q-bio.NC2026
Primate-like perceptual decision making emerges through deep recurrent reinforcement learning
Nathan J. Wispinski, Scott A. Stone, Anthony Singhal +2
Progress has led to a detailed understanding of the neural mechanisms that underlie decision making in primates. However, less is known about why such mechanisms are present in the…
cs.AI2022★ 5 cited
Adaptive patch foraging in deep reinforcement learning agents
Nathan J. Wispinski, Andrew Butcher, Kory W. Mathewson +3
Patch foraging is one of the most heavily studied behavioral optimization challenges in biology. However, despite its importance to biological intelligence, this behavioral optimiz…