Genetic Algorithms in games

Question

I have to do a term project on Genetic Algorithms, and I had the idea of tuning the traits (i.e. weapons to be used , etc) of a first person shooter bot. For example, I would represent the traits in the form of a string, with first 10 bits representing probability of choosing weapon1, next 10 bits representing probability of choosing weapon2, etc. I would thus get the optimal string and thus be able to figure out what should be the optimal set of weapons i should use.

The obvious problem that I am facing is how to find the fitness values. My idea would be that if I want to find the fitness of a string, I force the bot to use the corresponding weapons and play a game against it and use the final score of the bot as the fitness. The problem is that I would need to play a LARGE no of games.

Is there some sort of simulation that I can do? For example, can i somehow get a function f where I would feed in the bot's traits (ex : weapons, etc) and it would return the corresponding fitness values? Do open source FPS games provide such a library?

The other option would be to go into the source code of the game and then keep on simulating various scenarios and noting the score in each scenario. I would prefer not to have the added complexity of going into the source of the game, since this is a short(1 month) project.

Thanks.

Answer 1

I think your project is very complex for a one month project.

It's not quite so exciting but perhaps you could look at playing strategies for a board game or card game instead. This is a much simpler situation and and many games can easily and quickly be simulated allowing you to use a genetic algorithm to find a good playing strategy. It will teach you the principles of genetic algorithms without requiring you to understand the huge body of source code that would be necessary to simulate a first person shooter.