Remove real type

[strtr]

Andrei Alexandrescu Wrote:

> On 04/24/2010 04:30 PM, strtr wrote:
> > Andrei Alexandrescu Wrote:
> >
> >> On 04/24/2010 12:52 PM, strtr wrote:
> >>> Walter Bright Wrote:
> >>>
> >>>> strtr wrote:
> >>>>> Portability will become more important as evo algos get used
> >>>>> more. Especially in combination with threshold functions.
> >>>>> The computer will generate/optimize all input/intermediate
> >>>>> values itself and executing the program on higher precision
> >>>>> machines might give totally different outputs.
> >>>>
> >>>>
> >>>> You've got a bad algorithm if increasing the precision breaks
> >>>> it.
> >>>
> >>> No, I don't. All algorithms using threshold functions which have
> >>> been generated using evolutionary algorithms will break by
> >>> changing the precision. That is, you will need to retrain them.
> >>> The point of most of these algorithms(eg. neural networks) is
> >>> that you don't know what is happening in it.
> >>
> >> I'm not an expert in GA, but I can tell that a neural network that
> >> is dependent on precision is badly broken.
> > How can you tell?
> >
> >> Any NN's transfer function must be smooth.
> > http://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/cs11/report.html#Transfer%20Function
> >
> >  It wasn't for nothing I mentioned threshold functions
> >
> > Especially in the more complex spiking neural networks bases on
> > dynamical systems, thresholds are kind of important.
> 
> Meh. You can't train using a gradient method unless the output is smooth 
> (infinitely derivable).

Which was exactly why I mentioned evolutionary algorithms.