https://github.com/peteprattis/generic-planner-for-minigames

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.
https://github.com/peteprattis/generic-planner-for-minigames

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

Last synced: about 1 month ago
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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.

• Host: GitHub
• URL: https://github.com/peteprattis/generic-planner-for-minigames
• Owner: PetePrattis
• License: mit
• Created: 2019-12-10T19:35:43.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2019-12-10T19:47:13.000Z (about 5 years ago)
• Last Synced: 2024-11-17T11:54:09.061Z (3 months ago)
• 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
• Language: Python
• Size: 14.6 KB
• Stars: 1
• Watchers: 2
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# A Python and Artificial Intelligence Program / Project

**This is a Python project from my early days as a Computer Science student**

_This programm was created for the eighth semester class Distributed Artificial Intelligence -Intelligent Agents

and is the final project for the class_

> #### Description of project

>

>>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.

> #### A generic planner

>

>>A 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.


To 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.

> #### Implemented minigames

>

> 1. Blocks World

> 2. Water Jug problem

> 3. n - Puzzle

> #### About this project

>

> - The comments to make the code understandable, are within the .py archive

> - This project was written in Anaconda's Spyder IDE.

> - This program runs for Python version 2.7

> - This repository was created to show the variety of the work I did and experience I gained as a student

>