{"id":13435518,"url":"https://github.com/inoryy/tensorflow2-deep-reinforcement-learning","last_synced_at":"2025-05-08T00:39:44.745Z","repository":{"id":143805695,"uuid":"166591375","full_name":"inoryy/tensorflow2-deep-reinforcement-learning","owner":"inoryy","description":"Code accompanying the blog post \"Deep Reinforcement Learning with TensorFlow 2.1\"","archived":false,"fork":false,"pushed_at":"2021-08-12T19:39:54.000Z","size":97,"stargazers_count":207,"open_issues_count":2,"forks_count":50,"subscribers_count":8,"default_branch":"master","last_synced_at":"2025-05-08T00:39:38.965Z","etag":null,"topics":["a2c","advantage-actor-critic","deep-reinforcement-learning","keras","tensorflow","tensorflow2"],"latest_commit_sha":null,"homepage":"http://inoryy.com/post/tensorflow2-deep-reinforcement-learning/","language":"Jupyter Notebook","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/inoryy.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":"2019-01-19T20:42:29.000Z","updated_at":"2025-03-21T16:08:05.000Z","dependencies_parsed_at":null,"dependency_job_id":"c5c97f5a-f2ec-4920-8c3d-a949077d2dea","html_url":"https://github.com/inoryy/tensorflow2-deep-reinforcement-learning","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/inoryy%2Ftensorflow2-deep-reinforcement-learning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/inoryy%2Ftensorflow2-deep-reinforcement-learning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/inoryy%2Ftensorflow2-deep-reinforcement-learning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/inoryy%2Ftensorflow2-deep-reinforcement-learning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/inoryy","download_url":"https://codeload.github.com/inoryy/tensorflow2-deep-reinforcement-learning/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252978668,"owners_count":21834910,"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":["a2c","advantage-actor-critic","deep-reinforcement-learning","keras","tensorflow","tensorflow2"],"created_at":"2024-07-31T03:00:36.481Z","updated_at":"2025-05-08T00:39:44.714Z","avatar_url":"https://github.com/inoryy.png","language":"Jupyter Notebook","funding_links":[],"categories":["Jupyter Notebook","Sample Codes / Projects \u003ca name=\"sample\" /\u003e ⛏️📐📁"],"sub_categories":["Reinforcement Learning \u003ca name=\"RL\" /\u003e🔮"],"readme":"# Deep Reinforcement Learning with TensorFlow 2.1\n\nSource code accompanying the blog post\n[Deep Reinforcement Learning with TensorFlow 2.1](http://inoryy.com/post/tensorflow2-deep-reinforcement-learning/).\n\nIn the blog post, I showcase the `TensorFlow 2.1` features through the lens of deep reinforcement learning\nby implementing an advantage actor-critic agent, solving the classic `CartPole-v0` environment.\nWhile the goal is to showcase `TensorFlow 2.1`, I also provide a brief overview of the DRL methods.\n\nYou can view the code either as a [notebook](actor-critic-agent-with-tensorflow2.ipynb),\na self-contained [script](a2c.py), or execute it online with\n[Google Colab](https://colab.research.google.com/drive/1XoHmGiwo2eUN-gzSVLRvE10fIf_ycO1j).\n\nTo run it locally, install the dependencies with `pip install -r requirements.txt`, and then execute `python a2c.py`.  \n\nTo control various hyperparameters, specify them as [flags](https://github.com/inoryy/tensorflow2-deep-reinforcement-learning/blob/master/a2c.py#L12-L17), e.g. `python a2c.py --batch_size=256`.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Finoryy%2Ftensorflow2-deep-reinforcement-learning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Finoryy%2Ftensorflow2-deep-reinforcement-learning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Finoryy%2Ftensorflow2-deep-reinforcement-learning/lists"}