Thesis Topic Details

Topic ID:
3560
Title:
General Game-Playing Robot
Supervisor:
Michael Thielscher
Research Area:
Artificial Intelligence, Robotics
Associated Staff
Assessor:
Claude Sammut
Topic Details
Status:
Active
Type:
R & D
Programs:
CS CE BIOM BINF SE
Group Suitable:
No
Industrial:
No
Pre-requisites:
COMP3411 Artificial Intelligence or COMP9417 Machine Learning
Description:
General game playing is the attempt to create a new generation of Artificial
Intelligence (AI) systems that can understand the rules of new games and then
learn to play these games without human intervention. Unlike specialised systems such as chess programs, a general game player cannot rely on algorithms that have been designed in advance for specific games. Rather, it requires a form of general AI that enables the player to autonomously adapt to new and possibly radically different problems.

This research project is concerned with the design and implementation of a
general game-playing robot - an autonomous systems that can understand
descriptions of new games and learn to play them in a physical game
environment. It involves programming a robot arm controller to manipulate different kinds of game pieces on game boards.

If successful, this research could be published in a high-profile conference or journal.
Comments:
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
 
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