For my Masters thesis I am working on a study with Dr. Yong Gao at UBC Okanagan on using Artificial Intelligence to aid in the creation of game levels. This will have you playing a simple platforming game and creating levels for that game using our editor. If you think this sounds interesting you can find more information on LiteTux.ca (redirects to the study site) between July 11th and July 31st.
Now that I have plugged my study, and humbly request that
you share the LiteTux.ca link with your friends, I will spend a bit of time
explaining what I am researching and how I got to the point I am currently at.
I was originally looking at machine learning techniques and applying it to
procedural content generation, which is known as PCGML (Procedural Content
Generation via Machine Learning). Procedural content generation is the
technique used to create new assets through computer algorithms and has been
seen in the genre known as rogue-likes but it's also been used in creation of
textures from art packages as well as music and sound effects amongst other
things.
The idea I had when I first started this research was that
if you trained a neural network with good levels then you may be able to get
the AI to produce similar looking levels from what it has learned about what
good levels are like. There have been several different types of neural
networks used to create levels with the ones I developed being LSTMs and autoencoders.
The one thing I noticed while experimenting with these was that they do produce
interesting game levels but they tend to be still obviously computer generated.
My thoughts were that it would be interesting if you could have a human and the
AI working together.
Now knowing I was probably not the first person to come to
this conclusion, I started looking into this idea and found that there were
several editors known as mixed initiative Co-creative editors used for
predominantly strategy and dungeon romps but a few other genres were present.
The two main forms of editors where ones where the AI would make suggestions as
the user edited and ones where the user in the AI took turns editing. I
preferred the idea of suggestions so the editor I developed was set up so that
as the user made changes to the map the AI would use it's techniques to make
suggestions for how to improve the map well procedurally generating areas of
the map that the user hasn't had yet to edit. One thing I did notice about most
of these generators their editors is that the ones that did use machine
learning approaches tended to use evolutionary genetic algorithms. This led to
the basic idea for this study which was to see how using deep learning
techniques compared to using genetic algorithms for editing and if one of the
two techniques produced better overall results.
The game that I was focusing my research on was it very
popular platform in game held by a very litigious company so knowing that that
I would be having people edit levels for the game would potentially have IP
issues. I looked into a clone of this game and found the open source SuperTux
game. Unfortunately it was not as easy to compile and get running as I would
have liked and had way too many features in there that my editor would not be
able to support so I decided to clone the clone creating a simplified version
of Super Tux which I called LiteTux. Well this is not the greatest game I have
created and is probably a little bit too simplified I think that with a little
bit more Polish (such as finishing the animation which I simply did not have
time to complete) it would be pretty good game in fact may end becoming a much
better game as once the study is completed I plan on not only releasing the
game but the editor as open source with the hope that my research on mixed
initiative editing will be useful to other people and by other people I mean
general programmers not just academia.
Even if the study ends up the flaming disaster I fear it may
become due to lack of enough participants finishing the study, I am going to
continue to work on both the LiteTux game and the editor even if it is on my
own I may apply some of the techniques that I've learned towards other genres.
One of the things I am thinking about is my old Mr. Holman game and using at
least some of the utilities in the editor to make creating levels for that game
more enjoyable. Mr. Holman is on my list of projects that I do want to complete
so don't be surprised if next year you see a new version of Mr. Holman with the
interactive editor that makes suggestions for you and lets you share levels
with your friends.
I hope you enjoyed this brief overview of my research and
will support the study or at least tell other people that you think may be
interested in the study about it. I will keep you updated on what's happening
in future posts but no matter what the results the study the game and editor
will live on in one form or another.
