A2C and PPO implementations

该数据集包含了为深度强化学习实验修改过的PyTorch实现的A2C和PPO算法。此外，数据集还包括了用于实验的修改代码以及生成图表、研究不同优化器和超参数影响的工具。该任务旨在对连续控制任务中的策略梯度方法中的梯度下降优化器进行实证分析。This dataset contains PyTorch-implemented A2C and PPO algorithms modified for deep reinforcement learning experiments. Furthermore, the dataset includes modified experimental code and tools for generating charts and studying the impacts of different optimizers and hyperparameters. The core objective of this dataset is to conduct an empirical analysis of gradient descent optimizers in policy gradient methods for continuous control tasks.