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https://github.com/iris-hunkeler/fairghosts

Implementation of ant colony [ACO] controlled ghosts for Ms. Pac-Man competition for a 2016 IEEE publication.
https://github.com/iris-hunkeler/fairghosts

ant-colony-optimization ieee publication

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Implementation of ant colony [ACO] controlled ghosts for Ms. Pac-Man competition for a 2016 IEEE publication.

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# fairGhosts — Ant colony controlled ghosts for Ms. Pac-Man

This repository contains the code on which the publication [fairGhosts — Ant colony controlled ghosts for Ms. Pac-Man](https://ieeexplore.ieee.org/document/7744325)
is based.

The code developed for **fairGhosts** is found in the package `pacman/entries/ghosts/fair`.

### How to run the game
The game can be tested by running the `main method `pacman/Executor`.

Different run modes of the game can be used depending on configuration of the main method.

Default setting is:
* **Ghost Controller**: fairGhosts
* **Ms. Pac-Man Controller**: human interaction
* tracing of ghost decision is shown (this means that the planned path of each ghost is visually displayed)

## Background
### Ant Colony Optimization
[Ant Colony Optimization [ACO]](https://www.researchgate.net/publication/308953674_Ant_Colony_Optimization) is a metaheuristic inspired by the behaviour of ants foraging for food.
It can be applied to many different optimization problems than can use an incremental approach to build a solution.

### Ms. PacMan Competition
The game engine used is from the *Ms. Pac-Man vs. Ghost Competition* held during the IEEE World Congress on Computational Intelligence (WCCI 2012).