{"id":18249957,"url":"https://github.com/giulic3/flatland-challenge-marl","last_synced_at":"2025-04-04T16:31:03.143Z","repository":{"id":77447599,"uuid":"195676767","full_name":"giulic3/flatland-challenge-marl","owner":"giulic3","description":"Proposed solution to the Flatland challenge (https://www.aicrowd.com/challenges/flatland-challenge), solving the Vehicle Rescheduling Problem (VRSP) on trains using Multi-Agent-Reinforcement-Learning","archived":false,"fork":false,"pushed_at":"2020-01-22T17:03:56.000Z","size":39703,"stargazers_count":12,"open_issues_count":2,"forks_count":0,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-03-20T15:11:54.448Z","etag":null,"topics":["deep-q-learning","deep-reinforcement-learning","multi-agent-reinforcement-learning","pytorch"],"latest_commit_sha":null,"homepage":"","language":"Python","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/giulic3.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","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":"2019-07-07T17:03:22.000Z","updated_at":"2025-02-21T02:20:47.000Z","dependencies_parsed_at":null,"dependency_job_id":"fcd6c76a-d7b1-4c6e-a2cb-80aded9db16c","html_url":"https://github.com/giulic3/flatland-challenge-marl","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/giulic3%2Fflatland-challenge-marl","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/giulic3%2Fflatland-challenge-marl/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/giulic3%2Fflatland-challenge-marl/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/giulic3%2Fflatland-challenge-marl/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/giulic3","download_url":"https://codeload.github.com/giulic3/flatland-challenge-marl/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247209289,"owners_count":20901745,"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":["deep-q-learning","deep-reinforcement-learning","multi-agent-reinforcement-learning","pytorch"],"created_at":"2024-11-05T09:41:57.559Z","updated_at":"2025-04-04T16:31:03.137Z","avatar_url":"https://github.com/giulic3.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# flatland-challenge-marl\nThis repository contains the code issued to the Flatland competition in the structure explained in the \n[flatland-challenge-starter-kit](https://github.com/AIcrowd/flatland-challenge-starter-kit).\n\nThe relevant directories are:\n* cnn_globalobs - contains an approach based on CNN and (custom) global observations\n* fc_treeobs - contains an approach based on tree observations (for both single and multi-agent setting)\n* src/ - contains code with graph observations and local observations\n* src/rainbow/ - contains code of [Rainbow](https://arxiv.org/abs/1710.02298) for multi-agent systems.\n\n\n## Acknowledgements\n\nThe code for Rainbow was adapted to MAS from [Kaixhin/Rainbow](https://github.com/Kaixhin/Rainbow).","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgiulic3%2Fflatland-challenge-marl","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgiulic3%2Fflatland-challenge-marl","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgiulic3%2Fflatland-challenge-marl/lists"}