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Implementation of A* and BFS algorithms with custom heuristics in the scope of a vacuum learning agent with graphical interface.

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Vacuum Agent

GIF demo

About

This project is a demonstration of the implementation of a vacuum agent based on the Belief Desire Intention (BDI) formalism with the A* algorithm in Python. It was made in collaboration with Justin Aubin for a course in Artificial Intelligence at UQAC.

Options

To choose the exploration strategy, you have to open the file "config.py" and choose the mode "informed" or "not_informed" in the key "mode".

  • Informed uses A* algorithm with a custom heuristic close to what we call a "heatmap". The closer you get to an area dense with dust and jewelry, the lower the cost.
  • Non-informed simply uses Breadth-First Search with Manhattan distance heuristic.

How to use

# Clone this repository
$ git clone https://github.com/Wazzabeee/vacuum-agent/

# Go into the repository
$ cd vacuum-agent

# Install requirements
$ pip3 install -r requirements.txt

# Run the app
$ python main.py

About

Implementation of A* and BFS algorithms with custom heuristics in the scope of a vacuum learning agent with graphical interface.

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