{"id":16705511,"url":"https://github.com/rejuvyesh/fvmcts_experiments","last_synced_at":"2026-03-18T21:36:28.580Z","repository":{"id":150147965,"uuid":"332351232","full_name":"rejuvyesh/FVMCTS_experiments","owner":"rejuvyesh","description":"Experiments for https://arxiv.org/abs/2101.04788","archived":false,"fork":false,"pushed_at":"2021-04-30T04:11:55.000Z","size":20,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-01-21T05:43:25.297Z","etag":null,"topics":["multiagent-planning"],"latest_commit_sha":null,"homepage":"https://sites.google.com/stanford.edu/fvmcts/","language":"Julia","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/rejuvyesh.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-01-24T02:28:45.000Z","updated_at":"2021-04-30T04:11:57.000Z","dependencies_parsed_at":"2023-04-19T22:30:39.464Z","dependency_job_id":null,"html_url":"https://github.com/rejuvyesh/FVMCTS_experiments","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rejuvyesh%2FFVMCTS_experiments","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rejuvyesh%2FFVMCTS_experiments/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rejuvyesh%2FFVMCTS_experiments/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rejuvyesh%2FFVMCTS_experiments/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rejuvyesh","download_url":"https://codeload.github.com/rejuvyesh/FVMCTS_experiments/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243573165,"owners_count":20312879,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["multiagent-planning"],"created_at":"2024-10-12T19:30:35.991Z","updated_at":"2026-01-02T00:33:18.658Z","avatar_url":"https://github.com/rejuvyesh.png","language":"Julia","funding_links":[],"categories":[],"sub_categories":[],"readme":"# FVMCTS_experiments\n\n## Setup\nEnsure you have julia installed. Then clone this repository somewhere:\n\n```bash\ngit clone https://github.com/rejuvyesh/FVMCTS_experiments\n```\n\nEnsure that you are in the experiment directory:\n```bash\ncd FVMCTS_experiments\n```\n\nThen run in the terminal:\n```bash\njulia --project 'using Pkg; Pkg.instantiate(); Pkg.resolve()'\n```\n\nNow you are all set to run the scripts for running the experiments.\n\n## SysAdmin\n\nFor evaluating the `random` planner on the `ring` sysadmin domain with `global` rewards for `8` agents over `100` runs, and storing the results in `/tmp/logdir`:\n```bash\njulia --project run_sysadmin.jl ring_global 8 random 100 /tmp/logdir\n```\n\nSimilarly, for evaluating `maxplus` planner, with tree search depth as `3`, number of iterations of tree search as `20`, exploration constant as `5`, and maximum number of message passing iterations as `10`:\n```bash\njulia --project run_sysadmin.jl ring_global 8 maxplus 100 /tmp/logdir 3 20 5 10\n```\n\nFor evaluating `varel` planner with tree search depth as `3`, number of iterations of tree search as `20`, and exploration constant as `5`:\n```bash\njulia --project run_sysadmin.jl ring_global 8 varel 100 /tmp/logdir 3 20 5\n```\n\n## UAV Delivery\n\nFor evaluating the `random` planner on problem `1` (8 agents) over `100` runs, and stroing the results in `/tmp/logdir`:\n```bash\njulia --project run_uav.jl 1 random 100 /tmp/logdir\n```\n\nSimilarly, for evaluating the `maxplus` planner with tree search hyperparameters as used in the paper:\n```bash\njulia --project run_uav.jl 1 maxplus 100 /tmp/logdir\n```\nand `varel` planner:\n```bash\njulia --project run_uav.jl 1 varel 100 /tmp/logdir\n```\n\n**Note**: `varel` memory requirements are quite high and may run out of memory on larger problems.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frejuvyesh%2Ffvmcts_experiments","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frejuvyesh%2Ffvmcts_experiments","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frejuvyesh%2Ffvmcts_experiments/lists"}