No Free Lunch? (Delayed reply)

[Dimitris I. Tsioutsias]

> From: simonpe at aisb.ed.ac.uk
> Date: Wed, 8 Nov 1995 12:32:38 +0000
> ....
>
> I think the importance of the NFL theorem is that it destroys the idea
> that there's such a thing as a `super-powerful all-purpose general
> learning algorithm' that can optimize any problem quickly. Instead, if
> we want a learning algorithm to work well, we have to analyze the
> particular problems we're interested in and tailor the learning
> algorithm to suit. Essentially we have to find ways of building prior
> domain knowledge about a problem into learning algorithms to solve
> that problem effectively.
> .....


As any thoughtful person in the greater mathematical programming 
community might point out, there's no general optimization method
that could outperform any other on any kind of problem. Rather it's
the researcher's task to have an understanding of the problem domain, 
the computational requirements (and available resources), and the 
most intuitively promising avenue of attaining a ``good'' solution 
in the most efficient way...

--Dimitris