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FactoredValueMCTS

Scalable MCTS for team scenarios

https://github.com/juliapomdp/factoredvaluemcts.jl

Science Score: 64.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ✓
    Academic publication links
    Links to: arxiv.org
  • ✓
    Committers with academic emails
    1 of 3 committers (33.3%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (10.6%) to scientific vocabulary

Keywords

mcts multiagent-planning multiagent-systems
Last synced: 6 months ago · JSON representation ·

Repository

Scalable MCTS for team scenarios

Basic Info
  • Host: GitHub
  • Owner: JuliaPOMDP
  • License: mit
  • Language: Julia
  • Default Branch: master
  • Homepage:
  • Size: 273 KB
Statistics
  • Stars: 16
  • Watchers: 9
  • Forks: 3
  • Open Issues: 1
  • Releases: 3
Topics
mcts multiagent-planning multiagent-systems
Created over 5 years ago · Last pushed over 1 year ago
Metadata Files
Readme License Citation

README.md

FactoredValueMCTS

CI codecov.io Stable Dev

This package implements the Monte Carlo Tree Search (MCTS) planning algorithm for Multi-Agent MDPs. The algorithm factorizes the true action value function, based on the locality of interactions between agents that is encoded with a Coordination Graph. We implement two schemes for coordinating the actions for the team of agents during the MCTS computations. The first is the iterative message-passing MaxPlus, while the second is the exact Variable Elimination. We thus get two different Factored Value MCTS algorithms, FV-MCTS-MaxPlus and FV-MCTS-VarEl respectively.

The full FV-MCTS-MaxPlus algorithm is described in our AAMAS 2021 paper Scalable Anytime Planning for Multi-Agent MDPs (Arxiv). The FV-MCTS-Varel is based on the Factored Statistics algorithm from the AAAI 2015 paper Scalable Planning and Learning from Multi-Agent POMDPs (Extended Version) applied to Multi-Agent MDPs rather than POMDPs. We use the latter as a baseline and show how the former outperforms it on two distinct simulated domains.

To use our solver, the domain must implement the interface from MultiAgentPOMDPs.jl. For examples, please see MultiAgentSysAdmin and MultiUAVDelivery, which are the two domains from our AAMAS 2021 paper. Experiments from the paper are available at https://github.com/rejuvyesh/FVMCTS_experiments.

Installation

julia using Pkg Pkg.add("FactoredValueMCTS")

Citation

@inproceedings{choudhury2021scalable, title={Scalable Anytime Planning for Multi-Agent {MDP}s}, author={Shushman Choudhury and Jayesh K Gupta and Peter Morales and Mykel J Kochenderfer}, booktitle={International Conference on Autonomous Agents and MultiAgent Systems}, year={2021} }

Owner

  • Name: JuliaPOMDP
  • Login: JuliaPOMDP
  • Kind: organization
  • Location: Stanford University, University of Colorado Boulder

POMDP packages for Julia

Citation (CITATION.bib) 

@inproceedings{choudhury2021scalable,
  title={Scalable Anytime Planning for Multi-Agent {MDP}s},
  author={Choudhury, Shushman and Gupta, Jayesh K and Morales, Peter and Kochenderfer, Mykel},
  booktitle={International Conference on Autonomous Agents and Multiagent Systems (AAMAS)},
  year={2021},
  organization={IFAAMAS}
}

GitHub Events

Total
  • Issues event: 2
  • Watch event: 1
Last Year
  • Issues event: 2
  • Watch event: 1

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 16
  • Total Committers: 3
  • Avg Commits per committer: 5.333
  • Development Distribution Score (DDS): 0.5
Past Year
  • Commits: 6
  • Committers: 1
  • Avg Commits per committer: 6.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
rejuvyesh m****l@r****m 8
Dylan Asmar a****r@s****u 6
Shushman Choudhury s****y@g****m 2
Committer Domains (Top 20 + Academic)
stanford.edu: 1 rejuvyesh.com: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 3
  • Total pull requests: 5
  • Average time to close issues: 27 days
  • Average time to close pull requests: 6 months
  • Total issue authors: 3
  • Total pull request authors: 4
  • Average comments per issue: 2.33
  • Average comments per pull request: 3.6
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 2
Past Year
  • Issues: 1
  • Pull requests: 0
  • Average time to close issues: about 2 months
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 0
  • Average comments per issue: 0.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • dylan-asmar (1)
  • rejuvyesh (1)
  • JuliaTagBot (1)
Pull Request Authors
  • github-actions[bot] (2)
  • zsunberg (1)
  • rejuvyesh (1)
  • dylan-asmar (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads: unknown
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 3
juliahub.com: FactoredValueMCTS

Scalable MCTS for team scenarios

  • Versions: 3
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent repos count: 9.9%
Average: 27.4%
Forks count: 28.1%
Stargazers count: 32.6%
Dependent packages count: 38.9%
Last synced: 6 months ago

Dependencies

.github/workflows/CompatHelper.yml actions
  • julia-actions/setup-julia v1 composite
.github/workflows/Documentation.yml actions
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  • julia-actions/setup-julia v1 composite
.github/workflows/TagBot.yml actions
  • JuliaRegistries/TagBot v1 composite
.github/workflows/ci.yml actions
  • actions/checkout v4 composite
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  • julia-actions/cache v1 composite
  • julia-actions/julia-buildpkg v1 composite
  • julia-actions/julia-processcoverage v1 composite
  • julia-actions/julia-runtest v1 composite
  • julia-actions/setup-julia v1 composite