Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...

Traffic congestion, fuel consumption, and emissions also offer quantifiable performance indicators, making mobility uniquely ...

A recent study published in Engineering presents a significant advancement in manufacturing scheduling. Researchers Xueyan Sun, Weiming Shen, Jiaxin Fan, and their colleagues from Huazhong University ...

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

DeepSeek-R1's release last Monday has sent shockwaves through the AI community, disrupting assumptions about what’s required to achieve cutting-edge AI performance. Matching OpenAI’s o1 at just 3%-5% ...

A quadruped robot uses deep reinforcement learning to master walking on varied terrains, demonstrating energy-efficient and ...

Reinforcement learning frames trading as a sequential decision-making problem, where an agent observes market conditions, ...