OpenAi-Gym-CartPole-Acrobot-Solutions/policy_grad.py/ Jump to Cannot retrieve contributors at this time executable file139 lines (113 sloc)3.82 KB RawBlame importgym gym.logger.set_level(40) importnumpyasnp importmatplotlib.pyplotasplt defmain(): ...
The Gym API's API models environments as simple Python env classes. Creating environment instances and interacting with them is very simple- here's an example using the "CartPole-v1" environment: import gym env = gym.make("CartPole-v1") observation, info = env.reset(seed=42) for _ in ...
OpenAI gym就是这样一个模块,他提供给我们很多优秀的模拟环境。我们的各种强化学习算法都能使用这些环境。之前的环境都是用tkinter来手动编写,或者想玩玩更厉害的,像OpenAI一样,使用pyglet模块来编写。OpenAI gym官网:gym.openai.com/ 我们可以先看看OpenAI gym有哪些游戏:有2D的: 也有3D的: 本次将会以CartPole和...
The Gym API's API models environments as simple Pythonenvclasses. Creating environment instances and interacting with them is very simple- here's an example using the "CartPole-v1" environment: importgym env = gym.make("CartPole-v1") observation, info = env.reset(seed=42)for_inrange(1000...
A toolkit for developing and comparing reinforcement learning algorithms. - CartPole v0 · openai/gym Wiki
Cartpole: A pole is attached by an un-actuated joint to a cart, which moves along a frictionless track. The pendulum starts upright, and the goal is to prevent it from falling over by increasing and reducing the cart's velocity.(https://github.com/openai/gym/wiki/CartPole-v0) Pong: In...
cd gym sudo pip install -e .[all] 这里pip install -e .[all]是安装所有的environment,如果不想这么做可以pip install -e .安装基本项,之后手动安装所需要的environment。注意要使用管理员权限来安装,否则会报错! helloworld 安装完成后,我们运行一个小的demo验证是否顺利安装,这里用CartPole-v0下的1000帧验证...
我找不到关于OpenAI Gym环境'CartPole-v0'和'CartPole-v1'之间差异的确切描述。 这两个环境都有专门的官方网站(请参见1和2),尽管我只能在gym的github存储库中找到一个没有版本标识的代码(请参见3)。我还通过调试器检查了确切加载了哪些文件,它们似乎都加载了同一个文件。唯一的区别似乎在于它们内部分配的max_...
python anaconda jupyter-notebook openai-gym Anw*_*Roy 2022 03-26 1推荐指数 1解决办法 3211查看次数 使用DQN 增加 Cartpole-v0 损失 嗨,我正在尝试训练 DQN 来解决健身房的 Cartpole 问题。出于某种原因,损失看起来像这样(橙色线)。你们都可以看看我的代码并帮助解决这个问题吗?我已经对超参数进行了相当...
git clone https://github.com/openai/gym.gitcdgym pip install -e. If you prefer, you can do a minimal install of the packaged version directly from PyPI: pip install gym You'll be able to run a few environments right away: algorithmic ...