Bill Tozier wrote a very interesting article on how to be successful with evolutionary algorithms and machine 
learning, and how it applies to ExtremeProgramming.

http://groups.yahoo.com/group/extremeprogramming/message/45678

Excerpts:

"At every company I've ever visited, early on during my time there I have met a person in a position of decision-making power (call them the Expert) who says to me, 'Oh, one time I tried using <XXX>, but they don't work.'"

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See, I think many modern folks are used to thinking in terms of general-purpose tools, and the consequent ability to apply them liberally anywhere and always. They misunderstand the words "general purpose" to mean just that: good for what ails ye. But personally I think it's a ''fallacy'' to believe that what makes a tool "general-purpose" is its ability to work, without adjustment or adaptation, in a variety of settings. That, in fact, is what's ''provably'' wrong and misunderstood with the notion as it applies to the sordid world of machine learning.

What makes a tool -- or any approach to solving problems [What difference, really?] -- "general-purpose" is the ease with which one can:
* '''examine''' the tool's structure
* '''understand''' the reason for that structure in getting you to the goal
* '''make changes''' to that structure to cope with special circumstances
In short, '''adapt''' the tool.

''(Just go read the whole thing, there's too much good stuff to quote)''
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I'm surprised this is posted under the heading of an "EmergentProcess". I don't see how learning to use a tool is an emergent process.  Elaboration might help me understand how this is a good name for this page.

''Careful reading of the link and the material and the realization that all tools are not tools producing emergent artifacts might help you.'' 
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Related: ToolsProducingArtifact
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CategorySuccess