- 安装 OpenAI Gym 经典控制模块:运行 `pip install gym[classic_control]`。 - 如果遇到 NumPy 相关的弃用警告,升级 NumPy:运行 `pip install --upgrade numpy`。### 编写和运行代码 编写CartPole 示例代码: - 在您的主目录或喜欢的工作目录中,创建一个新的 Python 文件,例如命名为 `cartpole_example.py`。
● - 在您的主目录或喜欢的工作目录中,创建一个新的 Python 文件,例如命名为 `cartpole_example.py`。 ● - 使用文本编辑器打开这个文件,并写入以下 Python 代码: ● import gym ● # 创建并初始化 CartPole 环境,指定渲染模式 ● env = gym.make('CartPole-v1', render_mode='human') ● state = env...
● - 在您的主目录或喜欢的工作目录中,创建一个新的 Python 文件,例如命名为 `cartpole_example.py`。 ● - 使用文本编辑器打开这个文件,并写入以下 Python 代码: ● import gym ● # 创建并初始化 CartPole 环境,指定渲染模式 ● env = gym.make('CartPole-v1', render_mode='human') ● state = env...
reinforcement-learning deep-learning openai-gym pytorch dqn gym cartpole ddqn Updated Jul 25, 2024 Python thowell / optimization_dynamics Star 61 Code Issues Pull requests Implementation and examples from Trajectory Optimization with Optimization-Based Dynamics https://arxiv.org/abs/2109.04928 contr...
CartPole v0: openai/gym CartPole-v0 A pole is attached by an un-actuated joint to a cart, which moves along a frictionless track. The system is controlled by applying a force of +1 or -1 to the cart. The pendulum starts upright, and the goal is to prevent it from falling over. ...
env=gym.make('CartPole-v0').unwrapped # set up matplotlib is_ipython='inline'inmatplotlib.get_backend() ifis_ipython: fromIPythonimportdisplay plt.ion() # if gpu is to be used device=torch.device("cuda"iftorch.cuda.is_available()else"cpu") ...
gym.make('CartPole-v0').unwrappedenv=gym.make('CartPole-v0')plt.ion()# if GPU is to be useddevice=torch.device("cuda"iftorch.cuda.is_available()else"cpu")classReplayMemory(object):""" Define the replay memory settings """def__init__(self,capacity):self.capacity=capacity# Capacity ...
CartPole是http://gym.openai.com/envs/CartPole-v0/ 这个网站提供的一个杆子不倒的测试环境。 CartPole环境返回一个状态包括位置、加速度、杆子垂直夹角和角加速度。玩家控制左右两个方向使杆子不倒。杆子倒了或超出水平位置... 查看原文 【/强化学习7日打卡营-世界冠军带你从零实践/课程摘要和调参心得-No.5...
The overall framework we will be using is Ray/RLlib. Installing this (for example, withpip install ray[rllib]==0.8.5or via Anaconda) will bring in its dependencies, including OpenAI Gym. Perhaps the best thing to do with each new environment is to fire it up and take a look. If you...
MSE loss function Adam optimizer Performance CartPole-v0 defines "solving" as getting average reward of 195.0 over 100 consecutive trials. source Example trial gif Example trial chart Solved trials chart Author Greg (Grzegorz) Surma PORTFOLIO GITHUB BLOGAbout...