Tech Xplore on MSN

Reinforcement learning accelerates model-free training of optical AI systems

Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
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

Multi-Agent Evolutionary Reinforcement Learning Based on Cooperative Games

Abstract: Despite the significant advancements in single-agent evolutionary reinforcement learning, research exploring evolutionary reinforcement learning within multi-agent systems is still in its ...
IEEE

Continuous-Time Reinforcement Learning: New Design Algorithms With Theoretical Insights and Performance Guarantees

Abstract: Continuous-time reinforcement learning (CT-RL) methods hold great promise in real-world applications. Adaptive dynamic programming (ADP)-based CT-RL algorithms, especially their theoretical ...
GitHub

verl: Volcano Engine Reinforcement Learning for LLMs

verl is a flexible, efficient and production-ready RL training library for large language models (LLMs). verl is the open-source version of HybridFlow: A Flexible and Efficient RLHF Framework paper.
GitHub

yufeiwang63/RL-VLM-F

conda env create -f conda_env.yml conda activate rlvlmf conda install -y pytorch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1 cudatoolkit=11.3 -c pytorch pip install numpy==1.26.0 We use customized ...
BBC

Using materials - AQA Composite materials

It is often possible to separate the reinforcement from the matrix by physical processes. For example, reinforced concrete can be broken up using machinery. This is one stage in recycling the ...