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babyrobot-1.0.9
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مشاهده بیشترتوضیحات
An OpenAI Gym Environment for BabyRobot
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | babyrobot-1.0.9 |
| نام | babyrobot |
| نسخه کتابخانه | 1.0.9 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Steve Roberts |
| ایمیل نویسنده | steve@steveroberts.name |
| آدرس صفحه اصلی | https://github.com/WhatIThinkAbout/BabyRobotGym |
| آدرس اینترنتی | https://pypi.org/project/babyrobot/ |
| مجوز | MIT |
# BabyRobotGym
### A Reinforcement Learning Gym Environment for Baby Robot
The code in this repository accompanies the Towards Data Science article _[<b>Creating a Custom Gym Environment for Jupyter Notebooks</b> - <i>Part 1: Creating the framework</i>](https://towardsdatascience.com/creating-a-custom-gym-environment-for-jupyter-notebooks-e17024474617)_ and shows the steps required to create a custom gym environment with graphical output in a Jupyter notebook.
## To install:
```
pip install babyrobot
```
# Animation Example
An example notebook showing how animation and movie creation can be done in the Baby Robot Gym environment:
[](https://mybinder.org/v2/gh/WhatIThinkAbout/BabyRobotGym/HEAD?labpath=notebooks%2FBabyRobot_Animation.ipynb)
# API Example
The example notebook, showing all of the API calls used to create a Baby Robot Gym environment can be opened here:
[](https://mybinder.org/v2/gh/WhatIThinkAbout/BabyRobotGym/HEAD?labpath=notebooks%2FBabyRobot_API.ipynb)
# Reinforcement Learning
## Part 1: [State Values and Policy Evaluation](https://towardsdatascience.com/state-values-and-policy-evaluation-ceefdd8c2369)
[](https://mybinder.org/v2/gh/WhatIThinkAbout/BabyRobotGym/HEAD?labpath=notebooks%2FReinforcement%20Learning%2FPart%201%20-%20State%20Values%20and%20Policy%20Evaluation.ipynb)
### Training Example
An example of using the PPO Reinforcement Learning algorithm to train Baby Robot how to escape from a maze:
[](https://colab.research.google.com/github/WhatIThinkAbout/BabyRobotGym/blob/main/notebooks/PPO_Training.ipynb)
## Getting the Github Code:
### Testing
The test notebook, showing how to run a simple RL environment can be opened here:
[](https://colab.research.google.com/github/WhatIThinkAbout/BabyRobotGym/blob/main/baby_robot_gym_test.ipynb)
## Cloning the Github repository
To get up and running with this simple custom Gym Environment, do the following:
## 1\. <b><i>Get the code and move to the newly created directory</b></i>:
`git clone https://github.com/WhatIThinkAbout/BabyRobotGym.git` <br>
`cd BabyRobotGym`
* this directory contains the files and folder structure.
<br><br>
## 2\. <b><i>Create a Conda environment and install the required packages</b></i>:<br>
To be able to run our environment we need to have a few other packages installed, most notably '_Gym_' itself. To make it easy to setup the environment the Github repo contains a couple of '_.yml_' files that list the required packages.
To use these to create a Conda environment and install the packages, do the following (choose the one appropriate for your operating system):
On Unix:
`conda env create -f environment_unix.yml`<br>
On Windows:
`conda env create -f environment_windows.yml`<br>
<br><br>
## 3\. <b><i>Activate the environment</b></i>:
We've created the environment with all our required packages, so now it's just a case of activating it, as follows:
`conda activate BabyRobotGym`<br>
(when you're finished playing with this environment run "conda deactivate" to get back out)
<br><br>
## 4\. <b><i>Run the notebook</b></i>
Everything should now be in place to run our custom Gym environment. To test this we can run the sample Jupyter Notebook <i>'baby_robot_gym_test.ipynb'</i> that's included in the repository. This will load the _'BabyRobotEnv-v1'_ environment and test it using the Stable Baseline's environment checker.
To start this in a browser, just type:
`jupyter notebook baby_robot_gym_test.ipynb`<br>
(When running in jupyter notebook the current Conda environment will automatically be used and the required packages should all be available. It's also possible to run "<i>python -m ipykernel install --user --name=BabyRobotGym</i>" which will create a Jupyter Notebook kernel, that can then be selected from the notebook's menu.)
Or else just open this file in VS Code and make sure _'BabyRobotGym'_ is selected as the kernel. This should make the _'BabyRobotEnv-v1'_ environment, test it in Stable Baselines and then run the environment until it completes, which happens to occur in a single step, since we haven't yet written the 'step' function!
<br><br>
# Notes:
If, while running in a terminal (as opposed to a Jupyter Notebook) you get the warning "DeprecationWarning: Jupyter is migrating its paths to use standard platformdirs", in a terminal run:
`export JUPYTER_PLATFORM_DIRS=1`
followed by:
`jupyter --paths`
نیازمندی
| مقدار | نام |
|---|---|
| ==0.27.0 | gymnasium |
| ==0.11 | ipycanvas |
| ==2.23.0 | imageio |
نحوه نصب
نصب پکیج whl babyrobot-1.0.9:
pip install babyrobot-1.0.9.whl
نصب پکیج tar.gz babyrobot-1.0.9:
pip install babyrobot-1.0.9.tar.gz