{"id":16392285,"url":"https://github.com/m-romanenko/rl-quadcopter","last_synced_at":"2025-10-26T14:30:16.787Z","repository":{"id":240211971,"uuid":"155694179","full_name":"m-romanenko/RL-Quadcopter","owner":"m-romanenko","description":"Using Reinforcement Learning to teach a quadcopter how to fly ","archived":false,"fork":false,"pushed_at":"2019-01-12T15:24:02.000Z","size":242,"stargazers_count":5,"open_issues_count":0,"forks_count":3,"subscribers_count":2,"default_branch":"master","last_synced_at":"2024-05-17T10:55:36.759Z","etag":null,"topics":["ddpg","keras","python","reinforcement-learning"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/m-romanenko.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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":"2018-11-01T09:48:58.000Z","updated_at":"2024-05-17T10:55:41.283Z","dependencies_parsed_at":"2024-05-17T11:05:46.931Z","dependency_job_id":null,"html_url":"https://github.com/m-romanenko/RL-Quadcopter","commit_stats":null,"previous_names":["m-romanenko/rl-quadcopter"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/m-romanenko%2FRL-Quadcopter","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/m-romanenko%2FRL-Quadcopter/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/m-romanenko%2FRL-Quadcopter/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/m-romanenko%2FRL-Quadcopter/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/m-romanenko","download_url":"https://codeload.github.com/m-romanenko/RL-Quadcopter/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":219862822,"owners_count":16555951,"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":["ddpg","keras","python","reinforcement-learning"],"created_at":"2024-10-11T04:49:13.287Z","updated_at":"2025-10-26T14:30:16.394Z","avatar_url":"https://github.com/m-romanenko.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Deep RL Quadcopter Controller\n\n*Teach a Quadcopter How to Fly!*\n\nThis project contains code that designs an agent that controls a quadcopter, and trains it using the DDPG reinforcement learning algorithm. You can start by reading [this notebook](./Quadcopter_Project.ipynb). \n\n## References \n\n[Continuous control with deep reinforcement learning](https://arxiv.org/abs/1509.02971)\n\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fm-romanenko%2Frl-quadcopter","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fm-romanenko%2Frl-quadcopter","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fm-romanenko%2Frl-quadcopter/lists"}