Quote:Original post by Kylotan
A practical or industrial aim would be to use whichever method copes with the situation best, so you'd typically go for a tool that doesn't require such contortions to get it to work in all cases.

Let me begin by saying I agree with the OP's aim.

He said he's working on a final year research project. Key word is research. The whole point here is to try out something which is not commonly used in games (apparently), and see if he can improve on it. Perhaps find a fundamentally new way of using them. I admit I don't know that much about NNs, but I'm pretty sure people don't know EVERYTHING there is to know about them at this point. I'm sure innovation is still possible. And that doesn't happen if you don't attempt to improve on something that already exists, even if it was dismissed as an AI solution for games (perhaps prematurely, or maybe for good reasons).

Quote:You could potentially spend forever adjusting inputs, outputs, and hidden layers to try and get your neural network doing something useful, with no guarantee of getting anything that is good enough to be playable, or you can pick a method that explicitly accounts for all the scenarios a developer can envisage and get it working more reliably.

And what happens in a scenario that the developer did not originally envisage?

IMO, this is where the AI can come closest to 'making or breaking' the game - those unexpected but possible scenarios.

Quote:Again, the details of what you can really call AI is an academic concern. In industry the important thing is to get the agent doing what you want to meet the requirements of the game, not to get the agent thinking and perhaps doing something that you want in order to meet the requirements of some research into a method. If you're looking to real world implementations then they are invariably going to be driven by pragmatism.

Well, that certainly doesn't sit well with me, even if it is the reality. Personally, I wouldn't want to be a factory worker pumping out one game after anothre using nothing but previously known ideas and concepts, without the ability or any attempt to innovate.

You do bring up a good point, however. I now realize I wouldn't want to go into game development if it ends up involving nothing but spitting out cookie-cut, run-of-the-mill games.

To be honest I don't understand why ANN's are used at all. For the most part they are used as a glorified regression tool. I have spent a bit of time researching a few of the different networks and the only one that struck me as interesting was the Hopfield (If I remember correctly) network. I would be willing to bet 1000 bucks that if we just changed the name from ANN to something less suggestive, much less people would be interested.

I would love for someone to give me reasons why my opinion should change though.

Quote:Original post by sion5
Are NN's good or bad in games?

Certainly depends on the game. However, the common answer is "almost universally bad".

Why:

1) single-player "campaign" type games are very scripted environments. A very small subset of the rules design wants for the game I'm working on now:
- when the player destroys this Item, the AI will counter-attack.
- When the AI squad gets to 20% of its original units -> retreat.
- AI should only throw grenades when no other AI is throwing a grenade and has not for at least 10 seconds.
- Only 1-3 AI should ever rush the player at any given time
- AI should only spend 30% of their time hidden behind cover; further no single AI should remain hidden in cover for more than 3 seconds
- When the player's units get to a Point of Interest they should stop and play a canned set of animations at a specific point to develop the plot.

2) In a campaign environment design (and the player) want predictability. The point of game AI is not to be "smart" it is to be "fun". Fun means finding a way to exploit the AI so you can win every time. While encounters do not need to play out exactly the same they should play similarly enough that the player can learn how to beat it each time he plays the encounter and dies.

ANNs are really bad at both of those and are thus completely unsuitable for typical single-player type campaigns (aka Halo, Call of Duty 4, etc)

Things they are potentially useful for: fun interactive pets (Black & White's god avatar pet-thing), multi-player bots (there was a very sucessful Quake-bot driven by an ANN), some new genre of game.

Always remember the point of AI in games is to support that game's specific mechanics. If an ANN is the best choice then it's certainly ok to use it. It is, however, just a tool and as such is not going to be useful in many situations.

I think the project will be very interesting to you, but it's kind of representative of the chasm between academia and the professional game development world. In the former, the point of AI is to explore boundaries of flexible decision making. In the latter, the point of AI is to do exactly what the designer wants it to do.

-me