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multiagentpathfinding.jl

Structures and algorithms for Multi-Agent PathFinding in Julia

https://github.com/gdalle/multiagentpathfinding.jl

Science Score: 44.0%

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    Found CITATION.cff file
  • ✓
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    Scientific vocabulary similarity
    Low similarity (13.5%) to scientific vocabulary

Keywords

graph julia multi-agent pathfinding
Last synced: 6 months ago · JSON representation ·

Repository

Structures and algorithms for Multi-Agent PathFinding in Julia

Basic Info
Statistics
  • Stars: 15
  • Watchers: 2
  • Forks: 2
  • Open Issues: 2
  • Releases: 7
Topics
graph julia multi-agent pathfinding
Created almost 4 years ago · Last pushed 7 months ago
Metadata Files
Readme License Citation

README.md

MultiAgentPathFinding

Stable Dev Build Status Coverage Code Style: Blue

This package provides a toolbox for defining and solving multi-agent pathfinding problems in the Julia programming language.

Getting started

For the latest stable version, open a Julia Pkg REPL and run

julia pkg> add MultiAgentPathFinding

For the development version, run

julia pkg> add https://github.com/gdalle/MultiAgentPathFinding.jl

For now the documentation is a bit lacking, but take a look at the files in test for usage examples.

Background

MultiAgentPathFinding.jl contains basic optimization algorithms related to multi-agent pathfinding, as well as a parser for the standard benchmark instances and solutions described in

Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks, Stern et al. (2019)

Tracking Progress in Multi-Agent Path Finding, Shen et al. (2023)

If you use this package, please cite the following PhD dissertation:

Machine learning and combinatorial optimization algorithms, with applications to railway planning, Dalle (2022)

Related projects

Alternative solvers:

Owner

  • Name: Guillaume Dalle
  • Login: gdalle
  • Kind: user
  • Location: Lausanne
  • Company: EPFL

Postdoctoral researcher

Citation (CITATION.bib) 

@phdthesis{dalle:tel-04053322,
  title       = {{Machine learning and combinatorial optimization algorithms, with applications to railway planning}},
  author      = {Dalle, Guillaume},
  url         = {https://pastel.hal.science/tel-04053322},
  number      = {2022ENPC0047},
  school      = {{{\'E}cole des Ponts ParisTech}},
  year        = {2022},
  month       = Dec,
  keywords    = {Machine learning ; Combinatorial optimization ; Latent variable models ; Differentiable optimization layers ; Julia language ; Railway planning ; Apprentissage statistique ; Optimisation combinatoire ; Mod{\`e}les {\`a} variables latentes ; Couches diff{\'e}rentiables d'optimisation ; Langage Julia ; Planification ferroviaire},
  type        = {Theses},
  pdf         = {https://pastel.hal.science/tel-04053322v1/file/TH2022ENPC0047.pdf},
  hal_id      = {tel-04053322},
  hal_version = {v1}
}

GitHub Events

Total
  • Create event: 9
  • Commit comment event: 12
  • Release event: 4
  • Issues event: 3
  • Watch event: 4
  • Delete event: 7
  • Issue comment event: 18
  • Push event: 40
  • Pull request review event: 1
  • Pull request event: 15
  • Fork event: 1
Last Year
  • Create event: 9
  • Commit comment event: 12
  • Release event: 4
  • Issues event: 3
  • Watch event: 4
  • Delete event: 7
  • Issue comment event: 18
  • Push event: 40
  • Pull request review event: 1
  • Pull request event: 15
  • Fork event: 1

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 95
  • Total Committers: 1
  • Avg Commits per committer: 95.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 5
  • Committers: 1
  • Avg Commits per committer: 5.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Guillaume Dalle 2****e 95

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 8
  • Total pull requests: 18
  • Average time to close issues: 3 months
  • Average time to close pull requests: 27 days
  • Total issue authors: 4
  • Total pull request authors: 2
  • Average comments per issue: 1.38
  • Average comments per pull request: 0.94
  • Merged pull requests: 15
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 7
  • Average time to close issues: about 18 hours
  • Average time to close pull requests: about 7 hours
  • Issue authors: 1
  • Pull request authors: 2
  • Average comments per issue: 2.0
  • Average comments per pull request: 1.43
  • Merged pull requests: 5
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • gdalle (5)
  • scott2dd (1)
  • simsurace (1)
  • JuliaTagBot (1)
Pull Request Authors
  • gdalle (30)
  • simsurace (4)
Top Labels
Issue Labels
enhancement (3) bug (1)
Pull Request Labels

Dependencies

.github/workflows/CI.yml actions
  • actions/checkout v2 composite
  • codecov/codecov-action v2 composite
  • julia-actions/cache v1 composite
  • julia-actions/julia-buildpkg v1 composite
  • julia-actions/julia-docdeploy v1 composite
  • julia-actions/julia-processcoverage v1 composite
  • julia-actions/julia-runtest v1 composite
  • julia-actions/setup-julia v1 composite
.github/workflows/CompatHelper.yml actions
.github/workflows/TagBot.yml actions
  • JuliaRegistries/TagBot v1 composite
.github/workflows/register.yml actions
  • julia-actions/RegisterAction latest composite