Nature

Machine learning articles from across Nature Portfolio

Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...
IEEE

Generative Diffusion Model Enhanced MADRL for Distributed Flocking With Obstacle Avoidance of Fixed-Wing AAV Swarms

Abstract: The distributed flocking control of fixed-wing autonomous aerial vehicle (AAV) swarms in unknown and cluttered environments poses significant challenges due to their complex dynamics and ...
IEEE

Federated Deep Reinforcement Learning for Safe Multi-UAV Cooperative Control in IoT Communications

Abstract: The cooperative control of UAVs in a complex environment is the key and fundamental problem in intelligent transportation and IoT communication systems. The cooperative control policy of the ...
marktechpost

A Coding Implementation to Train Safety-Critical Reinforcement Learning Agents Offline Using Conservative Q-Learning with d3rlpy and Fixed Historical Data

In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment, generate a ...
GitHub

SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning

SkillRL is a framework that enables LLM agents to learn high-level, reusable behavioral patterns from past experiences. While traditional memory-based methods store redundant and noisy raw ...
GitHub

KernelGYM: A Gym for Kernel Generations

GPU Resource Management: Unlike CPU-bound code execution, kernel evaluation requires careful GPU memory management and device isolation. A single CUDA error can crash ...