OpenAIGym | Solving OpenAI Gym problems | Reinforcement Learning library

by shivaverma Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | OpenAIGym Summary

OpenAIGym is a Python library typically used in Artificial Intelligence, Reinforcement Learning applications. OpenAIGym has no bugs, it has no vulnerabilities and it has low support. However OpenAIGym build file is not available. You can download it from GitHub.

In this task we have to balance a rod on top of a cart. Number of action spaces is 2. Action space is discrete here. 0 - move cart to the left. 1 - move cart to the right. I solved this problem using DQN in around 60 episodes. Following is a graph of score vs episodes.

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OpenAIGym has a low active ecosystem.

It has 156 star(s) with 57 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 3 open issues and 4 have been closed. On average issues are closed in 61 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of OpenAIGym is current.

Quality

OpenAIGym has 0 bugs and 0 code smells.

Security

OpenAIGym has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

OpenAIGym code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

OpenAIGym does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

OpenAIGym releases are not available. You will need to build from source code and install.

OpenAIGym has no build file. You will be need to create the build yourself to build the component from source.

It has 990 lines of code, 91 functions and 17 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed OpenAIGym and discovered the below as its top functions. This is intended to give you an instant insight into OpenAIGym implemented functionality, and help decide if they suit your requirements.

Train the model
Train the optimizer
Predict target with given inputs
Train the objective function
Predict target
Calculate the gradient of the action gradients
Predict on inputs
Add an experience
Performs a single step
Soft update of the model
Sample from the buffer
Train DQN
Perform replay
Calculates the reward
Returns the action of the given state
Perform DAG
Calculate the action
Compute the Q learning score
Generate random policy

Get all kandi verified functions for this library.

OpenAIGym Key Features

No Key Features are available at this moment for OpenAIGym.

OpenAIGym Examples and Code Snippets

No Code Snippets are available at this moment for OpenAIGym.

Community Discussions

Trending Discussions on OpenAIGym

Trouble installing ns-3 gym

QUESTION

Trouble installing ns-3 gym

Asked 2021-Aug-30 at 15:00

I am trying to learn to work on ns-3 gym , the framework which helps in integrating openAigym and ns-3, by following the steps given here. But in the fourth step it says to install ns3gym from the src folder, the issue is that I'm not able to find the openaigym folder inside the src folder.

When I try to run the command it says not found. Command used:

...

ANSWER

Answered 2021-Aug-30 at 15:00

You must enter the path correctly on your computer after downloading the package to install.

for example:

Source https://stackoverflow.com/questions/68818941

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install OpenAIGym

You can download it from GitHub.
You can use OpenAIGym like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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