{"id":49865913,"url":"https://github.com/shiroonigami23-ui/omega","last_synced_at":"2026-05-15T03:00:03.876Z","repository":{"id":354926514,"uuid":"1224912602","full_name":"shiroonigami23-ui/omega","owner":"shiroonigami23-ui","description":"Beautiful modular D3QN research pipeline with training, ablations, plots, report, and packaging","archived":false,"fork":false,"pushed_at":"2026-04-30T23:30:40.000Z","size":5885,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-05-15T02:59:59.523Z","etag":null,"topics":["ablation-study","d3qn","gymnasium","pytorch","reinforcement-learning","research-pipeline"],"latest_commit_sha":null,"homepage":null,"language":"Python","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/shiroonigami23-ui.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,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2026-04-29T18:56:10.000Z","updated_at":"2026-05-06T10:02:32.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/shiroonigami23-ui/omega","commit_stats":null,"previous_names":["shiroonigami23-ui/omega"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/shiroonigami23-ui/omega","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/shiroonigami23-ui%2Fomega","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/shiroonigami23-ui%2Fomega/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/shiroonigami23-ui%2Fomega/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/shiroonigami23-ui%2Fomega/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/shiroonigami23-ui","download_url":"https://codeload.github.com/shiroonigami23-ui/omega/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/shiroonigami23-ui%2Fomega/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33051875,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-13T13:14:54.681Z","status":"online","status_checked_at":"2026-05-15T02:00:06.351Z","response_time":103,"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":["ablation-study","d3qn","gymnasium","pytorch","reinforcement-learning","research-pipeline"],"created_at":"2026-05-15T02:59:58.023Z","updated_at":"2026-05-15T03:00:03.865Z","avatar_url":"https://github.com/shiroonigami23-ui.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Project Omega: Full Delivery Repository\n\n![Python](https://img.shields.io/badge/Python-3.11-blue)\n![RL](https://img.shields.io/badge/Reinforcement%20Learning-D3QN-success)\n![Status](https://img.shields.io/badge/Status-Delivery--Packaged-brightgreen)\n\nThis repository contains the full packaged Project Omega delivery and extracted artifacts.\n\n## Included Delivery\n\n- `delivery_full/source_code/` complete source modules\n- `delivery_full/plots/` performance, distributions, ablation\n- `delivery_full/video/` agent GIFs\n- `delivery_full/reports/` research paper PDF + executive PPTX\n- `delivery_full/models/checkpoints/` saved checkpoints\n- `delivery_full/output/Project_Omega_Release.zip` packaged final artifact\n\n## Visual Preview\n\n![D3QN GIF](delivery_full/video/best_agent_d3qn.gif)\n\n![Performance Curve](delivery_full/plots/performance/performance_curve.png)\n\n![Ablation](delivery_full/plots/ablation/ablation_comparison.png)\n\n## Kaggle Save + Version\n\n1. Create a Kaggle Dataset and upload `Project_Omega_FULL_DELIVERY.zip`.\n2. Create a Kaggle Notebook with GPU enabled and attach that Dataset.\n3. Unzip in notebook:\n\n```python\n!unzip -q /kaggle/input/\u003cyour-dataset\u003e/Project_Omega_FULL_DELIVERY.zip -d /kaggle/working/omega\n```\n\n4. Save notebook version via Kaggle UI using **Save Version**.\n\n## Repository Layout\n\n```text\n.\n+-- delivery_full/\n+-- project_omega_m1_m2.py\n+-- project_omega_m3.py\n+-- project_omega_m4.py\n+-- project_omega_m5.py\n+-- project_omega_m6.py\n+-- project_omega_m7.py\n+-- project_omega_m8.py\n+-- requirements.txt\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshiroonigami23-ui%2Fomega","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fshiroonigami23-ui%2Fomega","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshiroonigami23-ui%2Fomega/lists"}