A quadruped robot uses deep reinforcement learning to master walking on varied terrains, demonstrating energy-efficient and ...
Automated healthcare IoT systems demand secure, low-latency, and energy-efficient computation—capabilities well-supported by fog computing. Effective selection of fog nodes is critical for maximizing ...
The path planning capability of autonomous robots in complex environments is crucial for their widespread application in the real world. However, long-term decision-making and sparse reward signals ...
According to God of Prompt on Twitter, DeepMind has published groundbreaking research in Nature led by David Silver, introducing an AI meta-learning system capable of autonomously discovering entirely ...
W4S operates in turns. The state contains task instructions, the current workflow program, and feedback from prior executions. An action has 2 components, an analysis of what to change, and new Python ...
[2025-09-28] 🎉 SPEC-RL Release! Official release of SPEC-RL with 2–3× rollout acceleration and seamless integration into PPO, GRPO, and DAPO workflows.
On a scorching July afternoon in Shanghai, dozens of Chinese students hunch over tablet screens, engrossed in English, math and physics lessons. Algorithms track every keystroke, and the seconds spent ...
Abstract: This study proposes a low-level radio frequency (LLRF) feedback control algorithm based on reinforcement learning (RL) using the soft actor–critic (SAC) and proximal policy optimization (PPO ...
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