增强学习的简单噪声环境增强（英文版）

英文标题：Simple Noisy Environment Augmentation for Reinforcement Learning中文摘要：本文介绍了针对强化学习 (RL) 的数据增强技术，旨在提高 RL 算法在不同环境下的表现效果，包括引入噪声、探索状态空间和改善训练数据的多样性。作者提出了两种新的增强技术，并在三种常用的 RL 算法和五个 MuJoCo 环境中进行实验研究，结果表明增强技术对增加回报有积极作用。英文摘要：Data augmentation is a widely used technique for improving model performancein machine learning, particularly in computer vision and natural languageprocessing. Recently, there has been increasing interest in applyingaugmentation techniques to reinforcement learning (RL) problems,