ATTENTION/WARNING - NE PAS DÉPOSER ICI/DO NOT SUBMIT HERE

Ceci est la version de TEST de DIAL.mem. Veuillez ne pas soumettre votre mémoire sur ce site mais bien à l'URL suivante: 'https://thesis.dial.uclouvain.be'.
This is the TEST version of DIAL.mem. Please use the following URL to submit your master thesis: 'https://thesis.dial.uclouvain.be'.
 

Machine learning for Smartphone games

Van Malleghem, Antoine ; Van Wallendael, Nicolas
(2016)

Files

Van_Malleghem_34151100_Van_Wallendael_73331000_2016.pdf
  • Open access
  • Adobe PDF
  • 23.78 MB
Download
Van_Malleghem_34151100_Van_Wallendael_73331000_2016_Annexe1.apk
  • Open access
  • Unknown
  • 26.13 MB
Download
Van_Malleghem_34151100_Van_Wallendael_73331000_2016_Annexe2.zip
  • Open access
  • Unknown
  • 1.87 MB
Download

Details

Supervisors
Dupont, Pierre
Faculty
Ecole polytechnique de Louvain
Degree label
Master [120] : ingénieur civil en informatique
Abstract
This thesis concerns the creation of an artificial player for a smartphone game able to learn the rules and how to win by itself thanks to Machine Learning techniques. The chosen game is an adaptation of the well known "rock-paper-scissors" game. The first step of this work is to clearly define the game with frameworks game theory and Machine Learning and to analyze the imposed constraint which is the smartphone hardware. The second step is to create the agent according to these frameworks by improving and assessing its performances. This part will also include the final results obtained and show that it can compete against a human.