With some hindsight - that is, one day's worth of hindsight - I must say that PPSN 2008 was one of the best conferences I've ever attended. On my very personal ranking, it's up there in the top with CIG 2007 in Hawaii. The organisation of PPSN was top-notch, with nothing going wrong, the food good, the opportunities for socialising/networking plentiful and the schedule adhered to (this is Germany, after all).
It's striking how high the quality of the papers are in PPSN. In Gecco and CEC you know and then find papers you think should not have been accepted in a scientific conference, but never so in PPSN. There is also a difference in "scientificness". Many papers at the two other major conferences present yet another variation on a well-known algorithm, or yet another application, with little in the way of analysis and comparison to the state of the art. At PPSN, the norm seems to be to isolate a particular phenomenon, parameter or operator of known algorithms and benchmarks and study it further, making sure that even papers that are not groundbreaking (which is by necessity most papers) add to the body of human knowledge.
Of course, there are new algorithms and applications at PPSN as well. In particular, a number of variants of the CMA-ES were presented. CMA-ES seems to have become the standard algorithm to benchmark continuous optimization algorithms against, which makes sense, as it reaches good result very quickly on many problems.
Speaking of benchmarks, there seems to be a consensus that there is a lack of good reinforcement learning benchmark. A poster by Marc Schoenauer even went so far as to list "Stop balancing the double pole!" among it's conclusion. Of course, I tried to convince everybody who brought up the topic that they should use simplerace instead. A much better benchmark in many ways.
Now I'm going to prepare the talk I'll give tomorrow (with Marie Gustafsson) on "AI from Science to Fiction" at the Fantastic Film Festival in Lund, and the talk I will give on Monday on "Computational Intelligence and Game Design" at ITU Copenhagen.
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Hi, Julian!
Very good your highlights from PPSN. I think you are the sole one posting about it. BUT, your informations from the front are very good.
Concerning CMA-ES, I admit it is a hard algorithm to implement, since it is necessary a good background in linear algebra, statistics, and calculus (of course). Eating and digesting all those maths is not an easy task. A CMA-ES book would be great.
Auf Wiedersehen!
Marcelo Augusto
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