Integrating deep reinforcement learning agents with the C. elegans nervous system
Chenguang Li,Gabriel Kreiman,Sharad Ramanathan · COSYNE 2022
Deep reinforcement learning (RL) has successfully trained machines to excel in video games, board games, and robotics. It has been argued that together, deep RL and robotics can be used to study biological learning by virtue of being embodied intelligence in the real world (Tan et al., 2021). In fact, RL itself was originally formulated to model animal behavior (Sutton & Barto, 1998). Here we go one step further and directly interface deep RL agents with a living neural network: that of the nematode C. elegans. We present a hybrid deep RL - C. elegans closed-loop computational system where
ePoster · Neuroscience