Re: SIGAda coverage in GCN

["Gene" <eugene.ressler@frontiernet.net>]

"Georg Bauhaus" <rm.tsoh.plus-bug.bauhaus@maps.futureapps.de> wrote in 
message news:4805107d$0$636$9b4e6d93@newsspool1.arcor-online.net...
> roderick.chapman@googlemail.com wrote:
>> On Apr 14, 3:59 pm, roderick.chap...@googlemail.com wrote:
>>> Today's new issue of GCN (athttp://www.gcn.com/print/27_8/46116-1.html)
>>
>> Interestingly, this article as just been picked up by SlashDot...
>
> As might have been expected, the article offers a lot to
> foster the stereotypes about the expensive language that
> drives weapons home; Ada is nothing more than Pascal, and
> not a word about the fundamental type system and concurrency
> until very late in the game.  So the least interesting remarks
> make it to the top. Oh well...

Oh well, indeed.  Leemon Baird is a good guy, but they are talking about my 
student Tyler Hallmark (at West Point, not the Air Force Academy) regarding 
the Connect 4 report.  Leemon's presentation - at least the one I saw - was 
about implementing a neural net and getting the same performance as C.

:-S

Tyler did some nice work for an undergrad effort.

ABSTRACT
Parallel evolution of game evaluation functions in ada
This is an Ada experience report, where we conclude that Ada tasking and 
distributed processing facilities make it a good research tool for 
experimentation with algorithms that might eventually need multiple 
processors. We implemented a genetic algorithm in Ada to create effective 
computer players for Connect4. Key to our success was employing Ada tasking 
and ALRM Annex E Distributed computing to harness a symmetric 
multiproces-sor and a distributed machine with very few code changes. Easy 
extension of an original single-task code to multi-tasking and distributed 
variants-even though extension was not planned in advance-was essential to 
timely completion. Using either the parallel or distributed implementation, 
about 150 processor hours were sufficient to evolve players that neither the 
GNU "Four-in-a-Row" Expert player nor the author could defeat. This 
algorithm relies on human expertise to restrict the genetic search space. 
Work is in progress on a new algorithm with near-zero encoded knowledge, 
which will run on 220 distributed nodes within the same distributed 
computing framework.