MIT researchers have introduced an efficient reinforcement learning algorithm that enhances AI's decision-making in complex scenarios, such as city traffic control. By strategically selecting optimal ...
MIT researchers developed an efficient approach for training more reliable reinforcement learning models, focusing on complex tasks that involve variability. This could enable the leverage of ...
Chlorophyll (a naturally occurring pigment involved in photosynthesis)-inspired molecules hold promise for developing next-generation light-harvesting materials. However, achieving precise control ...