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EvoDebates: Fit for the future - Applying the algorithm

Select a name or photograph to read the full position statement and to post your own comments.

photo: Ajith Abraham Ajith Abraham
"How well can EC adapt to the cluster/grid environment?"

photo: Thomas Bäck Thomas Bäck
"This is the key technology for dealing with data."

photo: Stefano Cagnoni Stefano Cagnoni
"GAs are quite well developed and are being accepted by industry as a viable design tool."

photo: Gusz Eiben Gusz Eiben
"I see a very promising line of research in EAs that calibrate themselves online, setting their own parameters for a given problem, while solving that problem."

photo: Peter Fleming Peter Fleming
"In my own communities I have advocated the use of EC on problems which, hitherto, were not susceptible to solution (or effective solution) by traditional approaches. This is by far the most exciting side of EC."

photo: Dario Floreano Dario Floreano
"A very promising area for EC is the manipulation of physical entities, such as robotics, electronics, molecules or bacteria."

photo: Terry Fogarty Terry Fogarty
"The most profitable development of new technology is in the development of tools dedicated to solving a class of problems such as time tabling."

photo: Carlos M Fonseca Carlos M Fonseca
"One of the areas I consider most promising for evolutionary algorithm research is decision support in general, and multi-objective optimisation in particular."

photo: Evan J Hughes Evan J Hughes
"We need to develop algorithms that can tackle the raw problems head on."

photo: Julian Miller Julian Miller
"A lot of people stress the importance of developing a theory of evolutionary computing. I would suggest, rather, that we use EC to expand our theoretical knowledge of particular problem areas."

blank photo Ian Parmee
"Evolutionary computing techniques need to be seen as optimal information gatherers rather than optimisation tools."

blank photo Colin Reeves
"The sort of problems appropriate for EAs are those whose fitness evaluation function is "difficult": computationally expensive, approximate in character or even largely subjective, affected by noise, having multiple criteria, dynamically varying etc."

photo: Marc Schoenauer Marc Schoenauer
"Evolutionary algorithms can be much more that yet another optimization method; they can provide a route to artificial creativity."

photo: Robert E Smith Robert E Smith
"'I asked the computer, and it gave me what seems like a pretty good answer' is a statement that sounds far less ridiculous and disappointing than it once might have."

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