{"id":18080641,"url":"https://github.com/omaraflak/reinforcement-learning-cpp","last_synced_at":"2025-04-12T14:21:54.309Z","repository":{"id":38784941,"uuid":"141569018","full_name":"omaraflak/Reinforcement-Learning-CPP","owner":"omaraflak","description":"Reinforcement Learning algorithm from scratch in C++.","archived":false,"fork":false,"pushed_at":"2018-07-19T11:29:00.000Z","size":7,"stargazers_count":14,"open_issues_count":0,"forks_count":1,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-03-26T08:51:36.646Z","etag":null,"topics":["cpp","from-scratch","neural-network","qlearning","reinforcement-learning"],"latest_commit_sha":null,"homepage":null,"language":"C++","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/omaraflak.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}},"created_at":"2018-07-19T11:18:53.000Z","updated_at":"2025-03-07T05:22:30.000Z","dependencies_parsed_at":"2022-09-18T04:00:23.924Z","dependency_job_id":null,"html_url":"https://github.com/omaraflak/Reinforcement-Learning-CPP","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/omaraflak%2FReinforcement-Learning-CPP","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/omaraflak%2FReinforcement-Learning-CPP/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/omaraflak%2FReinforcement-Learning-CPP/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/omaraflak%2FReinforcement-Learning-CPP/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/omaraflak","download_url":"https://codeload.github.com/omaraflak/Reinforcement-Learning-CPP/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248578877,"owners_count":21127717,"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":["cpp","from-scratch","neural-network","qlearning","reinforcement-learning"],"created_at":"2024-10-31T13:09:11.945Z","updated_at":"2025-04-12T14:21:54.276Z","avatar_url":"https://github.com/omaraflak.png","language":"C++","readme":"# Reinforcement Learning\n\nThis code demonstrates how to make a reinforcement learning algorithm from scratch in C++.\n\n# Download, Compile \u0026 Run\n\n```\ngit clone https://github.com/OmarAflak/Reinforcement-Learning-CPP\ncd Reinforcement-Learning-CPP\nmake\n./main\n```\n# Environment\n\nThe agent has to go from point A to point B.\n\n    A..........B\n    \nHe has two available commands : `left` and `righ`.\n\nThe reward policy is the following :\n\n* if (agent reaches point **B**) { reward=1 }\n* else { reward=0 }\n\n# Network\n\nAlthough the problem is very simple, I used a Neural Network to approach the **Q(s,a)** function.\n\nThe network takes the current state of the game as an input, and it outputs the **Q-value** for each possible action.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fomaraflak%2Freinforcement-learning-cpp","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fomaraflak%2Freinforcement-learning-cpp","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fomaraflak%2Freinforcement-learning-cpp/lists"}