{"id":31781222,"url":"https://github.com/giuse/dne","last_synced_at":"2025-10-10T08:34:36.265Z","repository":{"id":72054912,"uuid":"123926500","full_name":"giuse/DNE","owner":"giuse","description":"A set of neuroevolution experiments with/towards deep networks","archived":false,"fork":false,"pushed_at":"2019-12-31T12:47:23.000Z","size":50,"stargazers_count":125,"open_issues_count":3,"forks_count":10,"subscribers_count":5,"default_branch":"master","last_synced_at":"2024-01-23T09:59:50.166Z","etag":null,"topics":["rubyml"],"latest_commit_sha":null,"homepage":null,"language":"Ruby","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/giuse.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2018-03-05T13:52:40.000Z","updated_at":"2024-01-04T16:21:12.000Z","dependencies_parsed_at":"2023-04-28T12:17:12.536Z","dependency_job_id":null,"html_url":"https://github.com/giuse/DNE","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/giuse/DNE","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/giuse%2FDNE","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/giuse%2FDNE/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/giuse%2FDNE/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/giuse%2FDNE/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/giuse","download_url":"https://codeload.github.com/giuse/DNE/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/giuse%2FDNE/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":279003296,"owners_count":26083555,"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","status":"online","status_checked_at":"2025-10-10T02:00:06.843Z","response_time":62,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":["rubyml"],"created_at":"2025-10-10T08:31:40.342Z","updated_at":"2025-10-10T08:34:36.257Z","avatar_url":"https://github.com/giuse.png","language":"Ruby","readme":"# Deep Neuroevolution experiments\n\nThis project collects a set of neuroevolution experiments with/towards deep networks for reinforcement learning control problems using an unsupervised learning feature exctactor.\n\n## *Playing Atari with Six Neurons*\n\nThe experiments for this paper are based on [this code](https://github.com/giuse/DNE/releases/tag/six_neurons).  \nThe algorithms themselves are coded in the [`machine_learning_workbench` library](https://github.com/giuse/machine_learning_workbench), specifically using [version 0.8.0](https://github.com/giuse/machine_learning_workbench/releases/tag/0.8.0).\n\n\n## Installation\n\nFirst make sure the OpenAI Gym is pip-installed on python3, [instructions here](https://github.com/openai/gym).  \nYou will also need the [GVGAI_GYM](https://github.com/rubenrtorrado/GVGAI_GYM) to access GVGAI environments.\n\nClone this repository, then execute:\n\n    $ bundle install\n\n## Usage\n\n    bundle exec ruby experiments/cartpole.rb\n\n## Contributing\n\nBug reports and pull requests are welcome on GitHub at https://github.com/giuse/DNE.\n\n## License\n\nThe gem is available as open source under the terms of the [MIT License](https://opensource.org/licenses/MIT).\n\n## References\n\nPlease feel free to contribute to this list (see `Contributing` above).\n\n- **UL-ELR** stands for Unsupervised Learning plus Evolutionary Reinforcement Learning, from the paper _\"Intrinsically Motivated Neuroevolution for Vision-Based Reinforcement Learning\" (ICDL2011)_. Check [here](https://exascale.info/members/giuseppe-cuccu/) for citation reference and pdf.\n- **BD-NES** stands for Block Diagonal Natural Evolution Strategy, from the homonymous paper _\"Block Diagonal Natural Evolution Strategies\" (PPSN2012)_. Check [here](https://exascale.info/members/giuseppe-cuccu/) for citation reference and pdf.\n- **RNES** stands for Radial Natural Evolution Strategy, from the paper _\"Novelty-Based Restarts for Evolution Strategies\" (CEC2011)_. Check [here](https://exascale.info/members/giuseppe-cuccu/) for citation reference and pdf.\n- **Online VQ** stands for Online Vector Quantization, from the paper _\"Intrinsically Motivated Neuroevolution for Vision-Based Reinforcement Learning\" (ICDL2011)_. Check [here](https://exascale.info/members/giuseppe-cuccu/) for citation reference and pdf.\n- The **OpenAI Gym** is described [here](https://gym.openai.com/) and available on [this repo](https://github.com/openai/gym/)\n- **PyCall.rb** is available on [this repo](https://github.com/mrkn/pycall.rb/).\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgiuse%2Fdne","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgiuse%2Fdne","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgiuse%2Fdne/lists"}