A reinforcement learning framework that drives exploration through intrinsic curiosity achieved competitive performance against Proximal Policy Optimization (PPO) and the Intrinsic Curiosity Module (I…
A reinforcement-learning policy trained via Proximal Policy Optimization (PPO) achieved a 97.5% collision avoidance success rate in 1,000 deterministic Geosynchronous Equatorial Orbit (GEO) episodes, …
Researchers developed a reinforcement learning-based method for digital twin-driven bearing health monitoring that adaptively aligns simulated and real vibration data, achieving 92.8% cross-equipment …
A comprehensive review published on arXiv examines fine-tuning techniques for Large Language Models (LLMs), covering methodologies from supervised and unsupervised learning to parameter-efficient meth…