The applicability of computational intelligence and neural networks (NN) in games is a touchy subject here at AiGameDev.com, and in game developer forums generally. This is particularly interesting because everyone seems to be approaching the issue from a different direction:
Most developers starting out in game AI seem to gravitate towards neural networks by default. (I’m guilty of that myself!)
Developers with a certain level of experience in NNs tend to find classical game AI techniques more useful for typical problems.
With a solid background in machine learning, NNs become a very powerful tool when the application is right.
Rather than tiptoeing around the issue, this week’s developer discussion dives right in! (Remember you can win an AiGameDev.com T-Shirt this month by writing interesting comments…)
Neural networks have found a useful role in industry via data-mining, but games applications seem to be lagging.
Is the lack of NN applications in games a sign that there are no suitable problems?
Do game developers and designers lack the necessary skillset to apply NN?
Are NN missing some key technology that would allow more widespread adoption?
You’re welcome to discuss neural network technology in general, but keep in mind that single- and multi-layer perceptrons trained using back-propagation have had the most practical success in games to date.
Join the discussion by posting a comment below!
