{"id":15646173,"url":"https://github.com/scitator/papers","last_synced_at":"2025-09-06T18:43:22.103Z","repository":{"id":133293890,"uuid":"124503054","full_name":"Scitator/papers","owner":"Scitator","description":null,"archived":false,"fork":false,"pushed_at":"2018-06-18T09:20:47.000Z","size":15518,"stargazers_count":50,"open_issues_count":0,"forks_count":2,"subscribers_count":11,"default_branch":"master","last_synced_at":"2025-03-28T16:56:26.001Z","etag":null,"topics":["arxiv","deep-learning","deep-reinforcement-learning","papers","reinforcement-learning","reinforcement-learning-algorithms"],"latest_commit_sha":null,"homepage":null,"language":null,"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/Scitator.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":"2018-03-09T07:17:12.000Z","updated_at":"2024-01-04T16:21:19.000Z","dependencies_parsed_at":null,"dependency_job_id":"c3030ce5-182f-4996-ba63-1de38c15d0fb","html_url":"https://github.com/Scitator/papers","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/Scitator%2Fpapers","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Scitator%2Fpapers/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Scitator%2Fpapers/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Scitator%2Fpapers/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Scitator","download_url":"https://codeload.github.com/Scitator/papers/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246254150,"owners_count":20747949,"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":["arxiv","deep-learning","deep-reinforcement-learning","papers","reinforcement-learning","reinforcement-learning-algorithms"],"created_at":"2024-10-03T12:11:41.494Z","updated_at":"2025-03-29T23:15:06.638Z","avatar_url":"https://github.com/Scitator.png","language":null,"readme":"#### 2018-05\n- Progress \u0026 Compress: A scalable framework for continual learning [[arxiv](https://arxiv.org/abs/1805.06370)] \u0026 [[notes](https://github.com/Scitator/papers/blob/master/papers/1805_progress_compress.md)]\n- Playing hard exploration games by watching YouTube [[arxiv](https://arxiv.org/abs/1805.11592)] \u0026 [[notes](https://github.com/Scitator/papers/blob/master/papers/1805_youtube.md)]\n#### 2018-04\n- DORA The Explorer: Directed Outreaching Reinforcement Action-Selection [[arxiv](https://arxiv.org/abs/1804.04012)] \u0026 [[notes](https://github.com/Scitator/papers/blob/master/papers/1804_dora.md)]\n- Gotta Learn Fast: A New Benchmark for Generalization in RL [[arxiv](https://arxiv.org/abs/1804.03720)] \u0026 [[notes](https://github.com/Scitator/papers/blob/master/papers/1804_gotta_learn_fast.md)]\n\n#### 2018-03\n- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling [[arxiv](https://arxiv.org/abs/1803.01271)] \u0026 [[notes](https://github.com/Scitator/papers/blob/master/papers/1803_cnn_vs_rnn.md)]\n- Generative Multi-Agent Behavioral Cloning [[arxiv](https://arxiv.org/abs/1803.07612)] \u0026 [[notes](https://github.com/Scitator/papers/blob/master/papers/1803_behavioral_cloning.md)]\n- World Models [[arxiv](https://arxiv.org/abs/1803.10122)] \u0026 [[notes](https://github.com/Scitator/papers/blob/master/papers/1803_world_models.md)] \n- Semi-parametric Topological Memory for Navigation [[arxiv](https://arxiv.org/abs/1803.00653)] \u0026 [[notes](https://github.com/Scitator/papers/blob/master/papers/1803_sptm.md)] \n- A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay [[arxiv](https://arxiv.org/abs/1803.09820)] \u0026 [[notes](https://github.com/Scitator/papers/blob/master/papers/1803_smith_part1.md)] \n\n#### 2018-02\n\n- Model-Ensemble Trust-Region Policy Optimization [[arxiv](https://arxiv.org/abs/1802.10592)] \u0026 [[notes](https://github.com/Scitator/papers/blob/master/papers/1802_me_trpo.md)]\n\n#### 2018-01\n- Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor [[arxiv](https://arxiv.org/abs/1801.01290)] \u0026 [[notes](https://github.com/Scitator/papers/blob/master/papers/1801_soft_ac.md)]\n\n#### 2017-08\n\n- A Brief Survey of Deep Reinforcement Learning [[arxiv](https://arxiv.org/abs/1708.05866)] \u0026 [[notes](https://github.com/Scitator/papers/blob/master/papers/1708_rl_survey.md)]\n- Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control [[arxiv](https://arxiv.org/abs/1708.04133)] \u0026 [[notes](https://github.com/Scitator/papers/blob/master/papers/1708_reproducible_rl.md)]\n\n#### 2017-07\n- Distral: Robust Multitask Reinforcement Learning [[arxiv](https://arxiv.org/abs/1707.04175)] \u0026 [[notes](https://github.com/Scitator/papers/blob/master/papers/1707_distral.md)]\n\n#### 2017-03\n- Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks [[arxiv](https://arxiv.org/abs/1703.03400)] \u0026 [[notes](https://github.com/Scitator/papers/blob/master/papers/1703_maml.md)]\n\n#### 2017-02\n- Cognitive Mapping and Planning for Visual Navigation [[arxiv](https://arxiv.org/abs/1702.03920)] \u0026 [[notes](https://github.com/Scitator/papers/blob/master/papers/1702_cmp.md)]\n\n#### 2016-06\n- Progressive Neural Networks [[arxiv](https://arxiv.org/abs/1606.04671)] \u0026 [[notes](https://github.com/Scitator/papers/blob/master/papers/1606_progressive_nn.md)]","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fscitator%2Fpapers","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fscitator%2Fpapers","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fscitator%2Fpapers/lists"}