{"id":20430633,"url":"https://github.com/jihoonerd/continuous-control-with-deep-reinforcement-learning","last_synced_at":"2026-02-12T23:33:42.978Z","repository":{"id":40956811,"uuid":"334819014","full_name":"jihoonerd/Continuous-Control-with-Deep-Reinforcement-Learning","owner":"jihoonerd","description":"📖 Paper: Continuous control with deep reinforcement learning 🕹️","archived":false,"fork":false,"pushed_at":"2024-08-30T23:56:05.000Z","size":1491,"stargazers_count":5,"open_issues_count":2,"forks_count":1,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-09-12T01:30:48.024Z","etag":null,"topics":["atari","ddpg","lunarlander-v2","pytorch","reinforcement-learning"],"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/jihoonerd.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":"2021-02-01T03:27:23.000Z","updated_at":"2025-08-11T11:13:00.000Z","dependencies_parsed_at":"2023-01-22T05:15:49.193Z","dependency_job_id":"59eee094-ce2d-4911-84b7-abb0a35ef4de","html_url":"https://github.com/jihoonerd/Continuous-Control-with-Deep-Reinforcement-Learning","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/jihoonerd/Continuous-Control-with-Deep-Reinforcement-Learning","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jihoonerd%2FContinuous-Control-with-Deep-Reinforcement-Learning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jihoonerd%2FContinuous-Control-with-Deep-Reinforcement-Learning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jihoonerd%2FContinuous-Control-with-Deep-Reinforcement-Learning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jihoonerd%2FContinuous-Control-with-Deep-Reinforcement-Learning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jihoonerd","download_url":"https://codeload.github.com/jihoonerd/Continuous-Control-with-Deep-Reinforcement-Learning/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jihoonerd%2FContinuous-Control-with-Deep-Reinforcement-Learning/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29386222,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-12T22:07:52.078Z","status":"ssl_error","status_checked_at":"2026-02-12T22:07:49.026Z","response_time":55,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["atari","ddpg","lunarlander-v2","pytorch","reinforcement-learning"],"created_at":"2024-11-15T08:08:06.148Z","updated_at":"2026-02-12T23:33:42.948Z","avatar_url":"https://github.com/jihoonerd.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Continuous Control with Deep Reinforcement Learning (DDPG)\n\nThis implements a reinforcement learning algorithm [DDPG](https://arxiv.org/abs/1509.02971). Using the methodology employed for DQN, DDPG can resolve continous action space environments.\n\nFollowing shows that DDPG can solve one of the continuous action space environment in `OpenAI Gym`.\n\n|Episode: 0|Episode: 500|Episode: 900|\n|---|---|---|\n|![eps-0](assets/eps-0.gif)|![eps-500](assets/eps-500.gif)|![eps-900](assets/eps-900.gif)|\n\n## Score Graph for `LunarLanderContinuous-v2`\n\u003cimg src=\"assets/score_fig.png\" width=\"50%\" height=\"50%\"\u003e\n\n## Environments\n\n* Pytorch 1.7\n* Python 3.8\n\nPlease refer `requirements.txt` for python packages for this repo.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjihoonerd%2Fcontinuous-control-with-deep-reinforcement-learning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjihoonerd%2Fcontinuous-control-with-deep-reinforcement-learning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjihoonerd%2Fcontinuous-control-with-deep-reinforcement-learning/lists"}