fast-downward | Fast Downward is a domain-independent planning system | Runtime Evironment library

by danfis Python Version: Current License: No License

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

kandi X-RAY | fast-downward Summary

fast-downward is a Python library typically used in Server, Runtime Evironment, Nodejs applications. fast-downward has no bugs, it has no vulnerabilities and it has low support. However fast-downward build file is not available. You can download it from GitLab, GitHub.

Fast Downward is a domain-independent planning system. For documentation and contact information see

Support

Quality

Security

License

Reuse

Support

fast-downward has a low active ecosystem.

It has 7 star(s) with 0 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of fast-downward is current.

Quality

fast-downward has 0 bugs and 0 code smells.

Security

fast-downward has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

fast-downward code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

fast-downward 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

fast-downward releases are not available. You will need to build from source code and install.

fast-downward 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.

It has 39593 lines of code, 3030 functions and 442 files.

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

Top functions reviewed by kandi - BETA

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

Parse the command line arguments
Check that the mutex arguments are mutually exclusive
Convert time limit to integers
Set search options for an alias
Uncrustify files
Return a list of files matching the pattern
Call subprocesses
Run the diff between old and newfile
Convert a pddl to a SAS task
Translate the given task to a Prolog program
Compute a model
Translates a single task
Run the translation
Translate the given task into a Prolog program
Prints a usage description
Fill the categories
Pretty print a nested list
Compute the model
Run the validate function
Enqueue an effect
Build combinations
Check that the header files are in the same directory
Dump statistics about the task
Run the preprocessor
Return a dictionary of configuration options that can be optimized
Validate the condition
Translate a single task
Validate the equation
Run search

Get all kandi verified functions for this library.

fast-downward Key Features

No Key Features are available at this moment for fast-downward.

fast-downward Examples and Code Snippets

No Code Snippets are available at this moment for fast-downward.

Community Discussions

Trending Discussions on fast-downward

how to compile OpenCV with Fast-Downward

QUESTION

how to compile OpenCV with Fast-Downward

Asked 2017-Jan-08 at 11:59

I'm working on an academic research, implementing new search algorithms, based on Fast-Downward, a c++ open source that implement several Search Algorithms and many search domains and problems. Also installed Lab, a Python package that manage the compilation and the run scripting.

Recently I tried to include OpenCV library for its ML algorithms, in order to integrate those algorithms in my search algorithm.

But I encouraged some problems when including some libs in my FD project, and could not compile OpenCV with FD.

Project hierarchy:

...

ANSWER

Answered 2017-Jan-08 at 11:59

You should not need include(ML/CMakeLists.txt), add_subdirectory(ML) should be enough inside src/CMakeLists.txt.
Now, we can generally have two cases:

You have a system-wide installation of OpenCV (e.g. via apt-get, etc.), so you use the system version of OpenCV
You include the sources of OpenCV inside the project. You build it and you use this version of OpenCV.

These two cases need to be dealt with in slightly different ways.

System wide OpenCV installation

Let's assume OpenCV is installed somewhere in your system. Then in src/ML/CMakeLists.txt you should have some lines like the following:

Source https://stackoverflow.com/questions/41519477

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

Vulnerabilities

No vulnerabilities reported

Install fast-downward

You can download it from GitLab, GitHub.
You can use fast-downward 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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