Thesis Topic Details

Topic ID:
3435
Title:
Solving General Single-Player Games with Constraint Programming
Supervisor:
Michael Thielscher
Research Area:
Artificial Intelligence, Constraint Programming
Associated Staff
Assessor:
Toby Walsh
Topic Details
Status:
Active
Type:
R & D
Programs:
CS CE BIOM BINF SE
Group Suitable:
No
Industrial:
Pre-requisites:
COMP3411 Artificial Intelligence
Description:
General game players (GGPs) are computer systems able to play strategy games based solely on formal game descriptions supplied at "runtime" (in other words, they don't know the rules until the game starts). Unlike specialised game players, such as Deep Blue, general game players cannot rely on algorithms designed in advance for specific games; they must discover such algorithms themselves.

This project aims at building a GGP for single-player games based on Constraint Programming. It involves developing and implementing an automatic translation of general game descriptions for single-player games into suitable constraint programs.

If successful, this research could be published in a high-profile conference or journal.
Comments:
M. Genesereth, M. Thielscher. General Game Playing. Synthesis Lectures on Artificial Intelligence and Machine Learning 2014.
http://www.morganclaypool.com/doi/abs/10.2200/S00564ED1V01Y201311AIM024

M. Genesereth, N. Love, B. Pell: General Game Playing: Overview of the AAAI Competition, AAAI Magazine, Spring 2005.
http://logic.stanford.edu/classes/cs227/2014/readings/aaai.pdf
Past Student Reports
 
No Reports Available. Contact the supervisor for more information.

Check out all available reports in the CSE Thesis Report Library.

NOTE: only current CSE students can login to view and select reports to download.