The new reinforcement learning system lets large language models challenge and improve themselves using real-world data ...

Abstract: Evolutionary reinforcement learning (ERL), which integrates the evolutionary algorithms (EAs) and reinforcement learning (RL) for optimization, has demonstrated remarkable performance ...

In this tutorial, we explore advanced applications of Stable-Baselines3 in reinforcement learning. We design a fully functional, custom trading environment, integrate multiple algorithms such as PPO ...

Abstract: We report a newly developed room-temperature (RT) shimming method for high-temperature superconducting (HTS) magnets employing a deep Q-network (DQN), a type of reinforcement learning theory ...

Download PDF Join the Discussion View in the ACM Digital Library Deep reinforcement learning (DRL) has elevated RL to complex environments by employing neural network representations of policies. 1 It ...

口号：结合蓝图、节点图和代码；打通设计、开发、测试、构建和部署；跨领域开发前端、快速开发 MVP和学习前端的优质选择 ...

While advanced methods like VACE and Phantom have advanced video generation for specific subjects in diverse scenarios, they struggle with multi-human identity preservation in dynamic interactions, ...

What QeRL changes in the Reinforcement Learning (RL) loop? Most RLHF/GRPO/DAPO pipelines spend the bulk of wall-clock time in rollouts (token generation). QeRL shifts the policy’s weight path to NVFP4 ...