Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.

In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...

The adoption of physically simulated character animation in the industry remains a challenging problem, primarily because of the lack of the directability and generalizability of existing methods.

Over the last decade and a half, reinforcement learning models have fostered an increasingly sophisticated understanding of the functions of dopamine and cortico-basal ganglia-thalamo-cortical (CBGTC) ...

Deep reinforcement learning is having a superstar moment. Powering smarter robots. Simulating human neural networks. Trouncing physicians at medical diagnoses and crushing humanity’s best gamers at Go ...