[ACT-R-users] (no subject)

[A.Banks at surrey.ac.uk]

I have a quick newbie question which I wonder if anyone would be kind enough to help 
me out with. When fitting models to data it seems quite common to estimate one or two 
parameters in the model to maximise the fit; the fewer the better. What is the best or 
the conventional method for doing this? The online tutorials imply that the 
recommended approach is to try out different values until you get a good fit. But I'm 
concerned that with several parameters varying simultaneously I may not happen 
across the optimal fit. Also, this doesn't seem particularly theoretically motivated. Is 
there a better method?

Thanks very much,
Adrian