MAAC | Agent Reinforcement Learning '' ICML | Reinforcement Learning library

by shariqiqbal2810 Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | MAAC Summary

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

Code for "Actor-Attention-Critic for Multi-Agent Reinforcement Learning" ICML 2019

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Quality

Security

License

Reuse

Support

MAAC has a low active ecosystem.

It has 488 star(s) with 141 fork(s). There are 6 watchers for this library.

It had no major release in the last 6 months.

There are 10 open issues and 27 have been closed. On average issues are closed in 30 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of MAAC is current.

Quality

MAAC has 0 bugs and 0 code smells.

Security

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

MAAC code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

MAAC is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

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

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

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Create an AttentionSAC model
Prepare rollouts
Performs training
Save training data to file
Return the reward for a given agent
Returns the reward for a given agent
Calculates reward reward for the given world
Calculate the reward for the given world
Make a World object
Resets all accumulated rewards
Resets the world
Compute the probability of the DiscretePolicy
Generate one - hot actions from logits
Sample from probabilities
Run Gumbel softmax sampling
Sample from a Gumbel distribution
Sample from a Gaussian distribution
Provide observation information
Get the encoding of an agent
Update the state of the given world
Checks if agent is colliding
A worker that runs the worker
Reset all remotes
Test if agent is colliding
Wait for all environments to finish
Smoothly sample from logits

Get all kandi verified functions for this library.

MAAC Key Features

No Key Features are available at this moment for MAAC.

MAAC Examples and Code Snippets

No Code Snippets are available at this moment for MAAC.

Community Discussions

Trending Discussions on MAAC

How to generate count and percent for indicator variable?

How to make binary variables for multiple individuals in a certain cell?

QUESTION

How to generate count and percent for indicator variable?

Asked 2020-Oct-12 at 15:24

I am looking to create summary statistics that give a count and percentage for an indicator variable when another indicator is equal to 1. In the table below, I am looking to get a count of how many times NYAL 08B is equal to one and zero when NYAL 08 is equal to 1. Further, I am looking for a percentage of the time that NYAL 08B is equal to one when NYAL 08 is equal to one.

...

ANSWER

Answered 2020-Oct-12 at 15:24

You can use filter to keep only rows where NYAL 08 == 1 and use count to calculate number and prop.table for proportions.

Source https://stackoverflow.com/questions/64319862

QUESTION

How to make binary variables for multiple individuals in a certain cell?

Asked 2020-Oct-04 at 19:24

I am dealing with a bit of a wonky data frame. I'm working with a standard tabular data set/.csv file that is fairly standard for the most part, however, in one column every observation is a list of individuals. Here's how it looks:

...

ANSWER

Answered 2020-Oct-04 at 19:24

We can use cSplit_e from splitstackshape. It would get the output in a compact way in a single line

Source https://stackoverflow.com/questions/64198644

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

Vulnerabilities

No vulnerabilities reported

Install MAAC

You can download it from GitHub.
You can use MAAC 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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