{"id":25002249,"url":"https://github.com/pprattis/generic-planner-for-minigames","last_synced_at":"2025-03-29T20:44:21.888Z","repository":{"id":194621969,"uuid":"227200524","full_name":"pprattis/generic-planner-for-minigames","owner":"pprattis","description":"A python script that implements a generic planner to solve a series of minigames using heuristic algorithms to generate the best possible moves to reach the goal state.","archived":false,"fork":false,"pushed_at":"2019-12-10T19:47:13.000Z","size":15,"stargazers_count":1,"open_issues_count":0,"forks_count":2,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-02-04T21:44:21.008Z","etag":null,"topics":["artificial-intelligence","astar","astar-algorithm","astar-pathfinding","astar-search-algorithm","block-world","computer-science","generic-planner","heap","heuristics","n-puzzle","planner","program","python","student","water-jug-problem"],"latest_commit_sha":null,"homepage":null,"language":"Python","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/pprattis.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2019-12-10T19:35:43.000Z","updated_at":"2020-10-07T10:42:25.000Z","dependencies_parsed_at":"2023-09-14T10:27:46.710Z","dependency_job_id":null,"html_url":"https://github.com/pprattis/generic-planner-for-minigames","commit_stats":null,"previous_names":["peteprattis/generic-planner-for-minigames","pprattis/generic-planner-for-minigames"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pprattis%2Fgeneric-planner-for-minigames","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pprattis%2Fgeneric-planner-for-minigames/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pprattis%2Fgeneric-planner-for-minigames/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pprattis%2Fgeneric-planner-for-minigames/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pprattis","download_url":"https://codeload.github.com/pprattis/generic-planner-for-minigames/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246243567,"owners_count":20746307,"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":["artificial-intelligence","astar","astar-algorithm","astar-pathfinding","astar-search-algorithm","block-world","computer-science","generic-planner","heap","heuristics","n-puzzle","planner","program","python","student","water-jug-problem"],"created_at":"2025-02-04T21:40:40.763Z","updated_at":"2025-03-29T20:44:21.868Z","avatar_url":"https://github.com/pprattis.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# A Python and Artificial Intelligence Program / Project\n\n**This is a Python project from my early days as a Computer Science student**\n\n_This programm was created for the eighth semester class Distributed Artificial Intelligence -Intelligent Agents\nand is the final project for the class_\n\n\u003e #### Description of project\n\u003e\n\u003e\u003eA python script that implements a generic planner to solve a series of minigames using heuristic algorithms to generate the best possible moves to reach the goal state.\n\n\u003e #### A generic planner\n\u003e\n\u003e\u003eA planner generates a sequence of actions so that when the actions are executed the agent's world is found from an initial to a final state. The planner is considered generic when we change nothing in its code to solve different problems.\u003cbr\u003e\nTo generate the sequence of actions the planner uses a search algorithm to construct a search tree. The algorithm A star (A *) was used in this work.\n\n\u003e #### Implemented minigames\n\u003e\n\u003e 1. Blocks World\n\u003e 2. Water Jug problem\n\u003e 3. n - Puzzle\n\n\u003e #### About this project\n\u003e\n\u003e - The comments to make the code understandable, are within the .py archive\n\u003e - This project was written in Anaconda's Spyder IDE.\n\u003e - This program runs for Python version 2.7\n\u003e - This repository was created to show the variety of the work I did and experience I gained as a student\n\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpprattis%2Fgeneric-planner-for-minigames","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpprattis%2Fgeneric-planner-for-minigames","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpprattis%2Fgeneric-planner-for-minigames/lists"}