That's a very similar idea to our startup. Except we're not using brute force evolution algorithms. Which I think is a bad idea, for the same reason researchers have found neural networks to be generally a bad approach to machine learning. The problem is the same, while it might be mathematically viable to code a system that will brute force it's way to learn if a great game is. That takes too long to most commercial applications. Specially when it's so easy to "cheat" and pre-input some values you already learned yourself.
In short, why would you write a code that takes 10 years to learn something that you could teach it yourself in a few minutes?
Brute force evolution algorithms are a fun and interesting thing to do research on. But that's it. The only practical application for it, is to research the algorithms itself to better understand how they work! But I'm sure the author of Angelina knows this, as his main goal does seem to be better understand how the algorithms work. That's fine, just don't expect many awesome commercially viable games from it. If that was the goal, I'd recommend "cheating" your own knowledge and the knowledge of other players to train your machine learning algorithms, similar to a recommendation algorithm. That's what we're hoping to achieve ourselves.
Far from my area of expertise, but I always considered the reason to try the brute force approach was to uncover the non-obvious things that "everyone knows won't work".
Evolution is a pretty cool tool. That said, it has its limitations! Inventing brand new mechanics seems to be a particularly tricky problem, for instance. Look at something as left-field as Antichamber (from this year's IGF). That takes some creativity to come up with, I think.
Still, that's why it's research! Wouldn't be fun without feeling a bit impossible.
Not sure current technology is capable of yielding real creativity. Perhaps as we enter the era of quantum computing.
But fun level design and infinite gameplay generated using AI/ML techniques are a welcome addition to casual games.
Well, 'real creativity' is a tough thing to pin down or talk about at the best of times. I think it can be achieved with conventional computing, but I think many people would reject it as creative even when faced with it.
As you say, though, creative or not I'm just happy to be producing software that can make fun(-ish) games!
[+] [-] vibrunazo|14 years ago|reply
In short, why would you write a code that takes 10 years to learn something that you could teach it yourself in a few minutes?
Brute force evolution algorithms are a fun and interesting thing to do research on. But that's it. The only practical application for it, is to research the algorithms itself to better understand how they work! But I'm sure the author of Angelina knows this, as his main goal does seem to be better understand how the algorithms work. That's fine, just don't expect many awesome commercially viable games from it. If that was the goal, I'd recommend "cheating" your own knowledge and the knowledge of other players to train your machine learning algorithms, similar to a recommendation algorithm. That's what we're hoping to achieve ourselves.
[+] [-] michaelbuckbee|14 years ago|reply
[+] [-] unreal37|14 years ago|reply
I think it can. Will be interesting to see what games it produces.
[+] [-] mtrc|14 years ago|reply
Still, that's why it's research! Wouldn't be fun without feeling a bit impossible.
[+] [-] quasistar|14 years ago|reply
[+] [-] mtrc|14 years ago|reply
As you say, though, creative or not I'm just happy to be producing software that can make fun(-ish) games!