Fighting fires could be done remotely without the need to place firefighting crews directly in potentially dangerous situations by using collaborative teams of artificial intelligence-powered robots ...

Let’s look at how RL agents are trained to deal with ambiguity, and it may provide a blueprint of leadership lessons to ...

MIT researchers unveil a new fine-tuning method that lets enterprises consolidate their "model zoos" into a single, continuously learning agent.

EZMedTech.ai has received a 2026 Global Recognition Award for its healthcare scheduling automation platform that combines ...

From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have an important impact. That may feel especially true, for example, when ...

Wind turbine control systems have evolved significantly over the past decades, moving from simple classical controllers to sophisticated artificial intelligence-based strategies. Early utility-scale ...

According to @godofprompt, Meta has introduced DreamGym, a cutting-edge framework reshaping how AI agents learn through reinforcement learning. Traditional reinforcement learning has struggled with ...

Download PDF Join the Discussion View in the ACM Digital Library Deep reinforcement learning (DRL) has elevated RL to complex environments by employing neural network representations of policies. 1 It ...

Picture this: a self-driving car smoothly navigating treacherous mountain roads with consecutive hairpin turns – a scenario that would challenge even the most experienced human drivers. This vision is ...