Map-Elites-Evolutionary | Map-Elites based on Evolution Strategies

by uber-research Python Version: Current License: Non-SPDX

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kandi X-RAY | Map-Elites-Evolutionary Summary

Map-Elites-Evolutionary is a Python library typically used in Financial Services, Insurance applications. Map-Elites-Evolutionary has no bugs, it has no vulnerabilities, it has build file available and it has low support. However Map-Elites-Evolutionary has a Non-SPDX License. You can download it from GitHub.

best_policy.json: the json storing the parameters of the best controller, its performance, behavioral characterization and observation statistics (for input normalization). config.json: provides all the parameters for a given run. See config.py file for details of each parameter. out.logs: the output logs. results.csv: the csv collecting all the stats about the run. policies (folder) contains all policy files for each cell of the behavioral map, filenames are the cell ids. archive (folder) contains states about the archive.

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Support

Map-Elites-Evolutionary has a low active ecosystem.

It has 19 star(s) with 2 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

Map-Elites-Evolutionary has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Map-Elites-Evolutionary is current.

Quality

Map-Elites-Evolutionary has no bugs reported.

Security

Map-Elites-Evolutionary has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

Map-Elites-Evolutionary has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

Map-Elites-Evolutionary releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Top functions reviewed by kandi - BETA

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

Run optimizer
Add a new population
Logs observations statistics
Find the cell id associated to a given boundary
Save a policy to disk
Calculate objective for each population
Compute the gradient of the fitness function
Normalize fitness
Compute novelty and novelty
Collect results from a list of polynomials
Runs a sampling algorithm
Log iteration information
Logs observation statistics
Add a new individual
Calculate population results
Compute the novelty of a bcs
Collect the results from a list of polynomials
Run a Poisson rollout batch
Perform rollout on the model
Perform a single step
Compute the gradients of the fitness function
Resets the state of the model
Start a new training task
Run an eval_rollout batch
Start a single step
Perform a single step
Set up the configuration
Reset the model

Get all kandi verified functions for this library.

Map-Elites-Evolutionary Key Features

No Key Features are available at this moment for Map-Elites-Evolutionary.

Map-Elites-Evolutionary Examples and Code Snippets

No Code Snippets are available at this moment for Map-Elites-Evolutionary.

Community Discussions

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

Vulnerabilities

No vulnerabilities reported

Install Map-Elites-Evolutionary

You can download it from GitHub.
You can use Map-Elites-Evolutionary 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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