Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...
Reinforcement learning is a subset of machine learning. It enables an agent to learn through the consequences of actions in a specific environment. It can be used to teach a robot new tricks, for ...
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.
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 ...
For those unfamiliar, Reinforcement Learning (RL) is the science of decision making, specifically referring to how certain behaviors are encouraged, and others discouraged. It is one of three ...
Ryan Clancy is an engineering and tech (mainly, but not limited to those fields!!) freelance writer and blogger, with 5+ years of mechanical engineering experience and 10+ years of writing experience.
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