This is the repository I use to work on my thesis for the M.Sc. in Computer Science at Østfold University College.
It contains my documentation, my working files, as well as any code that is required for my work.
The tentative title of my thesis is "Evolving Entertaining NPCs" which probably tells you very little. In more descriptive terms, the aim of the thesis is to see whether artificial evolution can be used to create artificial intelligence for a game's opponents, with the aim of creating a more entertaining game. This will be accomplished using a system for doing such artificial evolution named ADATE, created by one of my supervisors, Dr. J. Roland Olsson.
The hypothesis I'm working from is that variation in game adversaries would create a more entertaining game than if all the adversaries behaved in a similar way, and that using artificial evolution makes it easy to create diverse AI for opponents that fulfill the criteria set for them, in this case entertainment value.
The specific focus of the thesis is to investigate if the use of inductive programming (via ADATE) can generate NPC AI that is interesting and diverse, and as such entertaining. To this end we base our experiments off Yannakakis thesis which utilized evolution on ANN.
The code for the testbed (a simple game) is Python using Pygame, the specifications for ADATE will be written in SML/ADATE-ML, the reports are written in LaTeX.