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"The Most Complex Piece of Engineering Known to Man"
- jey 19y agoOrgel's Second Rule: "Evolution is cleverer than you are." But that's just because humans are pretty stupid in the grand scheme of things.
- marcus 19y agoThats why I have always loved genetic algorithms. They are creating some patent worthy inventions using them now. Check John Koza's work. http://www.popsci.com/popsci/science/0e13af26862ba010vgnvcm1000004eecbccdrcrd/2.html http://www.popsci.com/popsci/science/0e13af26862ba010vgnvcm1...
- hhm 19y agoVery, very interesting link... thank you!
- pixcavator 19y agoGenetic algorithms are fun but let's not overhype them. They solve optimization problems by following an iteration procedure. And we all know that iteration commonly produces a _local_ maximum.
- marcus 19y agoTrue, but there are a host of techniques to skip local maximums, for example running several totally separate populations (families) for a certain number of generations and then creating a new population (family) based only on combinations from two other families. And a lot of times even the first local maximums are impressive. To see how powerful these things can be just compare using brute force random solutions to genetic algorithms you get results that are better by quite a few orders of magnitude. Or in short don't knock it till you've tried it. It isn't a universal solution for every problem and it can take quite a lot of work to correctly tweak with the fitness score and with all the variables but it is a very useful tool and can produce some very cool results.
- eru 19y agoThe local maximum problem has something to do with iteration?
- marcus 19y agoYes, iteration in this sense is basically traversing along a plane mostly in the direction of biggest gain. So you'll mostly traverse to local maximum, once you get to a local maximum, there is no evolutionary advantage to doing a step in any direction as they all lead to reduced performance which can cause you to miss a bigger maximum just around the corner. That is why all iterative algorithms suffer from local maximum problems.
- eru 19y agoDon't they use large populations of possible solutions for this very problem?
- sadiq 19y agoAre you sure you're not getting GAs mixed up with gradient descent? The whole point of a GA is that they're a global search. Mutation and crossover (with certain conditions) generally mean you don't get stuck in local maxima. Of course, there are conditions on that. The quality of your RNG, the probabilities of mutation/crossover, etc..
- pixcavator 19y agoMarcus replied to that http://news.ycombinator.com/item?id=90115 http://news.ycombinator.com/item?id=90115.
- sadiq 19y agoExactly. He's describing gradient descent (and possibly simulated annealing), not a genetic algorithm. Mutation, especially burst mutation with population stagnation, is what stops you getting stuck in local maxima.
- pixcavator 19y agoIt does not matter _how_ it is done, it is still an iteration. You may have several iterations going on but at best you can expect to find several local maxima - at any given time. Further, if there is no "stagnation", how do you know that you've found a solution?
- sadiq 19y agoStagnation is the case where the best individuals in the populations fitness hasn't increased by some value for a certain period of time. I'm not sure I understand what you mean by 'a solution'? You know you've not arrived at an acceptable solution when your fitness is below your required level. Granted, you never know there is a configuration with a fitness greater than your required fitness but this is generally considered when constructing the fitness function.
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- aswanson 19y agoPix, What is the liscence policy on the pixcavator SDK? If I wanted to incorporate some of your binaries into a product, what would be the cost?
- pixcavator 19y agoIt is free currently. Get in touch though. And thanks for a new name, I like it!
- cellis 19y agoCue Matrix
- mynameishere 19y agoIt's not a good comparison. In the very, very long-term, the "fit" inventions do tend to win out, but that says nothing about the processes by which they were built. That is, unless you get really loose with the definition. If I'm designing a bridge, and I come up with 10 blueprints, and select the best one...that's not really an evolutionary process, and neither would it be if 10 different engineers came up with a blueprint. If we build 10 bridges and wait for nine to collapse, well, that would be an evolutionary engineering process. (Again, over centuries and centuries, that very thing occurs.) A better analogy would be comparing the marketplace with a harsh environment. There, Linux survives for a mundane reason--just like mammals needed less heat from the atmosphere, linux needs less money from its customers. So, it may win out in the end.
- some 19y agoIts not a comparison at all. Linus replied to someone who said Linux coding style is not improving because no one sets the rules. Linus said that it is improving via evolution. Style liked by many will be taken over by others, style liked by few will fade out. Not a comparison. Just a fact.
- downer 19y agoYeah, but making a new "most complex piece of engineering" is fire-and-forget (at least if you move out of state and change your name). >apt-get install human-2.0 Building dependency tree Reading state information... Done After delivery $2.5 million will be used. Do you want to continue [Y/n]? n Abort.