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A simple search agent of an autonomous vacuum cleaner, trying to reach dirt spilled in different parts of a randomly generated room in the most efficient way possible. The project utilizes various search algorithms including, but not limited to; Greedy Search, Uniform Cost Search, and A* Search utilizing both path cost and a Manhattan heuristic.

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Daksh2060/vacuum-cleaning-simulator

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Vacuum Cleaning Simulator

This is a project template from UC Berkeley, for a simple search agent. This specific implementation sets a scenario, where the agent is an autonomous vacuum cleaner, trying to reach dirt spilled in different parts of a randomly generated room in the most efficient way possible. The project utilizes various search algorithms including, but not limited to; Greedy Best First Search, Uniform Cost Search, and A* Search utilizing both path cost and a Manhattan heuristic. The project displays both the search path and tiles visited for the vacuum to reach the different piles of dirt through a tkinter UI.

Features

  • Randomized Rooms: To be filled

  • Path and Node Display: To be filled

How does it work?

Algorithms

Installation and Use

Follow these steps to set up and run the Vacuum Cleaning Simulator:

  1. Download or clone the repository to your local machine:

    git clone https://github.com/Daksh2060/vacuum-cleaning-simulator

Contact

Feel free to reach out if you have any questions, suggestions, or feedback:

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A simple search agent of an autonomous vacuum cleaner, trying to reach dirt spilled in different parts of a randomly generated room in the most efficient way possible. The project utilizes various search algorithms including, but not limited to; Greedy Search, Uniform Cost Search, and A* Search utilizing both path cost and a Manhattan heuristic.

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