Google researchers introduce ‘Internal RL,’ a technique that steers an models' hidden activations to solve long-horizon tasks ...
Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
A quadruped robot uses deep reinforcement learning to master walking on varied terrains, demonstrating energy-efficient and ...
Among those interviewed, one RL environment founder said, “I’ve seen $200 to $2,000 mostly. $20k per task would be rare but ...
ADELPHI, Md. — Army researchers developed a pioneering framework that provides a baseline for the development of collaborative multi-agent systems. The framework is detailed in the survey paper ...
In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...
What if the very techniques we rely on to make AI smarter are actually holding it back? A new study has sent shockwaves through the AI community by challenging the long-held belief that reinforcement ...
Reinforcement learning frames trading as a sequential decision-making problem, where an agent observes market conditions, ...
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