Monday, October 7, 2013
my connectionist AI
Researchers who come from a traditional AI background (symbolic AI, g.o.f.a.i.) tend to avoid connectionist algorithms and view connectionism as competition. Many AI textbooks spend only a small number of pages on neural networks. Typical AI conferences may contain only a few neural network talks/papers. Coming from a physics and numerical computing background I had no such bias. Early on when I needed a nonlinear multivariable function approximation algorithm for my AI (Asa F 1.0) I was quite happy to try artificial neural network algorithms. My physics and math backgrounds also made me comfortable with continuous mathematics rather than discrete math (though I soon began to use both, even in one and the same program). I see connectionism as a useful source of algorithms.