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Programming IT Science Technology

Digital Darwin 253

An anonymous reader writes "Using genetic algorithms to breed strings of computer code graphically, this week's Nature magazine describes results from Caltech and Michigan State. Their program is Avida. While they mainly mimic mutation, not genetic cross-over [or inheritance (thus wiping away much memory of initial conditions)], their simulations show how a short-term backward step in survival strategies can generate innovative advances. It is not unlike running a maze which necessarily involves testing alot of dead-ends, and thus shares the graphical look of Conway's classic Game of Life." Here's a National Geographic story about this as well, or see their press release.
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Digital Darwin

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  • by sstory ( 538486 ) on Thursday May 08, 2003 @10:52AM (#5910143) Homepage
    And I wish everyone could see them at work. It's really kind of breathtaking how stumbling around in the parameter space, and filtering the bad missteps, can mimic the results of engineering. I think the minor problem of the small number of noisy anti-evolutionists would become even more minor. I mean, it's kind of hard to say that an algorithm doesn't work when you can compile a few thousand lines of c and then watch it work.
    • by jdevers77 ( 627410 ) on Thursday May 08, 2003 @11:02AM (#5910217)
      That makes the assumption that the anti-evolutionists are logical people. I would say that the many thousands of undisputable cases of evolution around us every day would also make them shut up, but it doesn't. Maybe when they are infected with antibiotic resistant Staph they will think about it from a different perspective...
      • That makes the assumption that the anti-evolutionists are logical people.

        Very true. And, in the case of using genetic algorithms as a point of evidence in an argument, this assumption works against you. For many people computers are a black box. If you say, "I have a computer program that models mysterious process X" it's just replacing something mysterious with something incomprehensible.

        And, before you do that, you have to assume that arguing is a productive activity in the first place. With many evolution deniers, it is not. But since they've wandered into my cave (the realm of logical, rational thought) I find it's my duty to eat them alive. :)
    • by Black Parrot ( 19622 ) on Thursday May 08, 2003 @11:04AM (#5910236)


      > I think the minor problem of the small number of noisy anti-evolutionists would become even more minor. I mean, it's kind of hard to say that an algorithm doesn't work when you can compile a few thousand lines of c and then watch it work.

      Yeah, as soon as I saw the article I thought, "How many evolution deniers will we dredge up this time?".

      It would be nice if someone had an on-line hub linking to all the GAs that are free and source-available, so that people could download one and try it themselves, look at the code if they suspected the answer was cheated in, and maybe tweak some parameters to see that both mutation and selection are actually needed for such systems to work. (The evolution deniers on talk.origins are fond of attacking mutation and selection independently, as if one or the other should be sufficient according to the theory of evolution.)

      Of course, some puppies would deny peeing on the floor even as you rubbed their nose in it, but we might as well inform those who are informable on matters of science.

      • by aborchers ( 471342 ) on Thursday May 08, 2003 @11:14AM (#5910311) Homepage Journal
        I enter the fray reluctantly.

        The first thought I had when I saw the article (presented on Space.com as "Darwin Proved Right ...") was that simulating something in a computer does not necessarily prove anything about the physical world. We can synthesize all sorts of things that have no analogy in nature. EA, AI, are fascinating fields inspired by evolutionary theory, but I fail to see how executing a computer program that assumes evolution in its infrastructure proves anything but that modelling evolution in software works.

        For the record, I am not anti-evolution, though I may occassionally be noisy...

        • > The first thought I had when I saw the article (presented on Space.com as "Darwin Proved Right ...") was that simulating something in a computer does not necessarily prove anything about the physical world. We can synthesize all sorts of things that have no analogy in nature. EA, AI, are fascinating fields inspired by evolutionary theory, but I fail to see how executing a computer program that assumes evolution in its infrastructure proves anything but that modelling evolution in software works.

          Yes,


          • Yes, they shouldn't say "Darwin Proved Right" (for several reasons).


            Well said, and I assume you would put "irreducible complexity" cheif among them.

            It's ridiculous that in the 21st century we have to tread so carefully over the biases, misconceptions, and agendas in presenting science.

            • > > Yes, they shouldn't say "Darwin Proved Right" (for several reasons).

              > Well said, and I assume you would put "irreducible complexity" cheif among them.

              No, "irreducible complexity" is utter bunkum made up by Behe to give a pseudo-scientific veneer to his underlying "I don't see how it could happen" argument.

              If you want to know how many times the IC argument against biological evolution has been refuted, ask about it on talk.origins. The only interesting research question that IC gives rise

              • by sstory ( 538486 )
                Speaking of this topic, my favorite anti-evolutionist thing is the 'analogy' of evolution to a tornado in a junkyard putting together a plane. What a piece of junk that argument is. I think you have to laugh about anti-evolution things, or you'll just get depressed about humanity.
              • I can't be sure it's dishonesty--I've known people who forced themselves to believe some creationism stuff in order to remain christians. There's an old creationism case, Edwards v Aguillard, which went to the supreme court. A 'friend of the court' brief was filed arguing that creationism was not science. It was signed by, among others, 72 Nobel Laureates.

                When 72 Nobel Laureates say your 'science' isn't science, your boat is sinking.

            • 'Irreducible complexity' is crap. What complex structure exists which does not contain any independently-useful substructure? None I've ever seen.
        • The first thought I had when I saw the article (presented on Space.com as "Darwin Proved Right ...") was that simulating something in a computer does not necessarily prove anything about the physical world.

          I completely agree. However, one of the most popular arguments against evolution is that complex, interdependent traits like the mechanism involved in poisonous snakebites, for example, cannot evolve through random mutation, since two "random" developments need to happen at once in the same indiv

        • Because the major reason people reject the idea is because they simply don't think it's plausible. Models may be simplified: but what they do demonstrate quite handily is the plausibility of some mechanism to accomplish what we suggest it can.
      • I was looking at GAs for a solution in a n parameter system in chemistry.

        Here's a nice collection of links and source codes I found back then: The Genetic Algorithm Archive [navy.mil]

    • by drooling-dog ( 189103 ) on Thursday May 08, 2003 @11:27AM (#5910416)
      Indeed. Given the way that genetic inheritance works -- e.g., with mutation, crossover recombination, etc. -- you could argue that evolution is a matter of mathematical necessity. But faith always trumps reason with the creationists, and so it's usually an exercise in exasperation to debate the issue, no matter how solid your arguments are. They will refuse to comprehend them as a point of principle.

      I've done some GA work myself, and it is quite fascinating. E.g., too high a mutation rate and the system destabilizes, but too low a rate and it never (or very slowly) finds its optimum fitness. Throw in some genetic recombination (simulating sexual reproduction) and evolution to higher mean levels of fitness accelerates considerably as useful "genes" are conserved while others quickly disappear. It's very cool.

      Modern creationists are in the same place that official Christiandom was in the time of Galileo, I think. If you're religious, nothing in modern biology (which largely is evolution) really denies a role for a deity in kickstarting the whole shebang. Setting up the system to run itself unattended, in fact, would have been the smart way to do it. Those who insist that God would create a system far inferior to this -- i.e., that requires endless hand-tweaking of every minute detail -- are really delivering Him a kind of insult, aren't they?

      • by gillbates ( 106458 ) on Thursday May 08, 2003 @12:06PM (#5910804) Homepage Journal
        Modern creationists are in the same place that official Christiandom was in the time of Galileo, I think. If you're religious, nothing in modern biology (which largely is evolution) really denies a role for a deity in kickstarting the whole shebang. Setting up the system to run itself unattended, in fact, would have been the smart way to do it. Those who insist that God would create a system far inferior to this -- i.e., that requires endless hand-tweaking of every minute detail -- are really delivering Him a kind of insult, aren't they?

        A point seemingly lost on a lot of right-wing fundamentalists. When you study religion, you notice certain trends, and one of these trends is that the oldest and most well established religions don't ask their believers to deny their intellectual capacities. The problem with "creation scientists" is the same problem with "evolutionary biologists" - each firmly believes in their position regardless of the weakness of the position or evidence to the contrary.

        Weak minds often have a hard time with the intelligent design arguments of creation. While we don't specifically deny evolution, we posit that there was a Creator who started the process, and has and does attend to his creation. When one looks at the complexity of living things compared to that of inanimate objects, one can't help but be struck by the difference in complexity between what merely exists and those things that grow.

        Interestingly, while this study can show the merits of evolution, it does more to bolster the intelligent design theory than to destroy it. While the experiment was very interesting, we must remember that the digital organisms did have an intelligent designer - it's not like the programs sprang to life on their own!

        • While we don't specifically deny evolution, we posit that there was a Creator who started the process, and has and does attend to his creation.

          Fine. Now who designed this Creator?

        • What the experiment actually shows is that complexity can evolve from simplicity. Thus, it is one more nail in the coffin of intelligent design since "the difference in complexity between what merely exists and those things that grow" could be merely a consequence of evolution.
        • by Black Parrot ( 19622 ) on Thursday May 08, 2003 @01:26PM (#5911492)


          > The problem with "creation scientists" is the same problem with "evolutionary biologists" - each firmly believes in their position regardless of the weakness of the position or evidence to the contrary.

          Could I trouble you to summarize the weakness of the position of evolutionary biologists and the contrary evidence? Presumably you have something beyond the same old tripe that has been refuted hundreds of times, or you wouldn't be saying that.

          > Weak minds often have a hard time with the intelligent design arguments of creation. While we don't specifically deny evolution, we posit that there was a Creator who started the process, and has and does attend to his creation.

          And that position is completely worthless as a way of understanding the universe, because it is compatible with any observation whatsoever.

          > When one looks at the complexity of living things compared to that of inanimate objects, one can't help but be struck by the difference in complexity between what merely exists and those things that grow.

          What measure of complexity are you using? I'd like to see your calculations showing the complexity of a squirrel and the complexity of the Nile delta.

          But maybe before we get into that too deeply... What has complexity got to do with anything? Are you making an underlying claim that complexity can only come about as a result of intelligent design? Is the Nile delta the result of intelligent design? Are intelligent designers the result of intelligent design? (Where did the first intelligent designer come from?)

          > Interestingly, while this study can show the merits of evolution, it does more to bolster the intelligent design theory than to destroy it. While the experiment was very interesting, we must remember that the digital organisms did have an intelligent designer - it's not like the programs sprang to life on their own!

          Yes, and our simulations of continental drift are written by humans too. Are we to conclude that humans are pushing the continents around?

          Study up on the concept of "non sequitur" when you have a little spare time.

        • Interestingly, while this study can show the merits of evolution, it does more to bolster the intelligent design theory than to destroy it.
          That doesn't really follow the argument far enough. A good discussion on this particular point is made as part of Robert J. Sawyer's novel Calculating God, in which alien beings come to earth as part of a scientific expedition to look for evidence of God.
    • So how many lines of code are you compiled from?
  • I like the choice of the smiley face. It is a lot like the Life Game, where you can kinda just watch it, knowing something kinda kewl is going on, but maybe not knowing excatly why.

    I like the red guys the best... kill them blue guys! Go red guys!

    M@
  • by olethrosdc ( 584207 ) on Thursday May 08, 2003 @10:53AM (#5910151) Homepage Journal
    Evoluationary Algorithms are quite common in Artificial Life projects. EAs are also used to solve engineering problems (as a multiple-solution stochastic search method), with remarkable success. There is another, similar project that is also extremely ambitious and whose source code has been released - it is called Tierra. Links to this and other similar projects can be found here [vub.ac.be].
  • Tierra (Score:3, Interesting)

    by Hayzeus ( 596826 ) on Thursday May 08, 2003 @10:54AM (#5910154) Homepage
    Anybody remember this one? Similiar idea -- each organism was a simple series of opcodes (think corewars) subject to mutation.

    Each "organism" would compete for RAM, the idea being to -- if not survive -- at least replicate itself. This was a pretty ambitious project at one point, but petered out at some point. I notice the Avida creators do give the original Tierra author, (Tom Ray) credit.


    • Corewars was a great experiment. I remember hacking the opcodes and studying countless games for a "better-than-Mouse" alternative.

      Because of the limitations on the environment, the complexity was grasp-able in a short amount of time.

      This also led to the maximization of the environmental space for the experiment. Adding more complexity extends this gameplay, but at the expense of making it less approachable to newcomers.

      These days, one could crank out a bot in Q3Arena and test it against the human play
  • by AndroidCat ( 229562 ) on Thursday May 08, 2003 @10:54AM (#5910159) Homepage
    Anything that munches CPU time but produces cool graphics is a winner: Life, Fractals, now perhaps this.

    I'm not sure why the high CPU requirement is needed, but it seems true. As always, the real question is: Will it make a cool t-shirt?

    • by jefu ( 53450 )
      I had a genetic algorithm type of thing a while back that could be used to selectively evolve images under user control and it produced some really cool pictures that I thought would have made great t-shirts. But I never actually tried to make one that way. If I'd had an easy way to actually make a shirt from the image though I'd probably have made quite a few and handed them out.
  • No, sir...uh...I'm not playing Liquid War instead of working!

    I'm...um, writing code! Yeah, that's right! It's self-replicating and evolutionary stuff. No, sir, it's not a virus! It's just a game! Ah...I mean, integrated development environment.
  • game of life (Score:5, Informative)

    this page [math.com] give a better overview of the game of life if you are not familiar with it (as well as a john conway pic).

    especially because it demonstrates some of the classice patterns that have been identified that lead to long lasting/ interesting cellular automata.

    their little java applet is really nice too because of the way it works: you can populate it with some of the notable pattern generators (hit open in the upper left corner) and then play it out in superspeed and watch the magic.

    i am not affiliated with them at all btw!
  • by Davak ( 526912 ) on Thursday May 08, 2003 @11:01AM (#5910214) Homepage
    I have been trying to develop a way of using the internet as my AI database. I am running small individual programs which pseudomutate and change... and the ones that perform the best are allowed to continue to run. The main goal is to use the internet (google, for example) as a foundation of knowledge.

    If anybody else has any useful links, please pass them on.


    Commonsense -- Web Based Human Input to Create AI (Allows download of sample of database) [mit.edu]

    AI and AL source code [clg-net.com]

    Web interface for synonym sets [princeton.edu]

  • Does that mean we can now get Digital Darwin Awards?
  • by pubjames ( 468013 ) on Thursday May 08, 2003 @11:10AM (#5910274)
    I was really into this stuff about a decade ago. Using evolutionary processes to get results is really amazing - it's something you have to see for yourself.

    What saddens me is how little progress is being made in this area. We still seem to be playing games drawing coloured dots in 2D space. When I was into this stuff, I envisaged we'd be designing cars, bridges, language translators, even soap powder boxes with evolution techniques by today. But it hasn't happened.

    Let me tell you, when you design a system that evolves, and you see it doing stuff you didn't intentionally program it to do, it gives you a real headrush. Evolution is a tool that we haven't learnt to use yet. The sad thing is, we don't even seem to be trying too hard. Perhaps I should get back into it...
    • I was really into this stuff about a decade ago.

      Damnit I've just read the summary of the article in Nature and I cannot believe that Nature published this. Or rather, I can't believe that they haven't published anything like this in the last few decades!

      God, this really makes me wish I'd stayed in the field. Do you know how many scientists long to get a paper published in Nature? Careers are built on it. And they get one published doing stuff that people have been doing for years.

      Damn and blast. Now I'
    • Scientific American last month had an article on the genetic-algorithm-based development of electronic circuits. It had some very interesting facts. Their genetic software has autonomously created duplicates of many of the long-standing basic patents in the field.

      And it hasn't stopped there. They've patented at least six new useful circuits that their algorithm has discovered.

      So, while genetic programming is not yet exactly widespread, I thought you'd be interested to know that those who are plying t

    • My opinion is that while applying mutation, crossbreeding and fitness selection to solve a problem only maps easily to simple problems.

      When you scale up to larger problems, like trying to evolve a program to parse a piece of code, you either have problems determining what kind of "fitness function" to use, or find that your evolved programs are fragile and only work for specific input, not generic.

      The real kicker, is to figure out how to make evolved programs less fragile and specialized.
      • My opinion is that while applying mutation, crossbreeding and fitness selection to solve a problem only maps easily to simple problems.

        I agree in the sense that we've only been able to map it to simple problems, but that's just because we're doing it wrong.

        The real kicker, is to figure out how to make evolved programs less fragile and specialized.

        Agreed.
    • I envisaged we'd be designing cars, bridges, language translators, even soap powder boxes with evolution techniques by today. But it hasn't happened.

      They [engineous.com] are used for many things, including tweeking the design of turbine airfoils (personal experience).

      The main reason they are not used more is that the analysis tools that have to be used with the EA are not perfect, you will almost always (without severe limitations on the available solution space) end up way of in some corner of the space where your pre
    • by adjuster ( 61096 ) on Thursday May 08, 2003 @12:13PM (#5910865) Homepage Journal

      When I was into this stuff, I envisaged we'd be designing cars, bridges, language translators, even soap powder boxes with evolution techniques by today. But it hasn't happened.

      Imagine "evolving" a language translator. How do you gauge the "effectiveness" of the perspective genomes? Compare their output to a "known good" output? Okay-- so do we have enough "known good outputs" that we can realistically test the performance of a perspective genome over a large set of problem cases? Who decides what is "good output"? How do you qualify that into a fitness factor? Language translation has too much subtlety and nuance to be gauged by simple fitness measurements. ("Oh, I know-- we'll just do a string comparasion between the perspective output and the 'known good'.")

      It would seem to me that in cases where the relative fitness of the perspective output is a function of many, many variables, that testing for fitness would become computationally unwieldy or impossible, and negate any positive benefit of using genetic algorithms.

      Problems that have easy, simply defined fitness factors are good candidates for GA's (think optimizing functions for execution speed or size, designing a structure to have the maximum possible load-bearing capacity), but problems that are not simply defined do not lend themselves well to GA's-- like, say, language translation.

      I think that GA's can provide novel solutions to reasonably simple problems, but the larger, harder problems, need to be decomposed into smaller problems, where possible, rather than being approached as a composite problem.

      From an esthetic perspective, I think GA's are especially interesting, though. It's quite fun to make 'evolutionary decisions' in a GA-based image-creation program and see [netlink.co.uk] the results, or to listen to GA-based music creation [columbia.edu].

    • Well... Usually people use things like games with dots because they're spending more time on the code than on the interface... I mean, yes, you COULD represent it on screen with little robots running around shooting each other, but if it doesn't convey any more information than colored dots, why bother?

      Also, it's probably a mistake to automatically assume "games with dots = simplistic"... See the game of Go for a counterexample...
  • Biomorphs (Score:5, Informative)

    by rmolehusband ( 192640 ) on Thursday May 08, 2003 @11:13AM (#5910297)
    Anyone ever read The Blind Watchmaker (Richard Dawkins) and try to code up the biomorphs example? There's at least on
    example [syr.edu] on the web.
  • From the text ...

    While they mainly mimic mutation, not genetic cross-over [or inheritance (thus wiping away much memory of initial conditions)

    Mutation?

    no genetic Cross over?

    Sounds like a lot of coders that I know.

  • by AlphaMaker ( 556605 ) on Thursday May 08, 2003 @11:14AM (#5910316)
    In Electronic Design Automation software, there is a similar technique which is used called simulated annealing. It goes on the idea of modifying input parameters in order to converge on an "optimal" solution. In order to get past local-optimum solutions, every so often some parameters are modified in a controlled pseudo-random way.

    While the specifics are different, the general concept is the same.

    • Annealing and 'spin-glass' models are commonly used when describing neural networks, one of the AI trends that hasn't gotten a lot of press lately, because like many others, it's still years away from doing something practical for people in their everyday lives or truly miraculous like simulated vision.

      Another self-modifying piece of engineering was discussed recently which was an attempt to give a computer that could self-modify circuitry to "evolve" an oscillator, by giving it the waveform as a goal.

      It
  • by freality ( 324306 ) on Thursday May 08, 2003 @11:17AM (#5910334) Homepage Journal
    Tierra was by Tom Ray, a pioneer in the AL field. It was a great idea, but failed to turn around with interesting biodiversity. You'd create creatures, they'd optimize themselves, some variants and parasites would evolve, but then things would simmer down within a few hours and you'd be in a steady state for ever.

    Network Tierra was Ray's response to this. It was supposed to allow a "Cambrian explosion" of biodiversity, by providing tons of (networked computer) space for the little creatures to explode into, and then specialize, in. This led to interesting migration behavior, and one of my all-time favorite web-pages [atr.co.jp], but it too failed to spark that je ne sais quois, that spark of life.

    Anyways, it did spark Avida and the Digital Life Lab at Cal Tech. Avida is essentially a deeper look at the fundamentals behind AL. In Tierra, I think the design philosophy was something like "make it look a lot like a living ecological system and the life-force will appear out of the ether", and actually, Tierra was a great leap forward beyond more mundane genetic programming a la John Koza.

    Avida, on the other hand, is much more systematic in exploring the parameter space (which is large and sensitive) for setting up an AL system. This turned out to be fruitful, as Adami found that only when certain, very narrow, environmental conditions were met would the little creatures start outsmarting that Creationist boogeyman, the Second Law of Thermodynamics.

    Turns out that Tierra didn't have spatiality (needed to be more restrictive on who could sleep with who) and mutation rates (some power law math that's way over my head) set right.

    But the real punch-line to this whole story is that the direct beneficiary of these insights in Microsoft! Hah!

    Microsoft was funding Adami's work because Windoze crashed too much. They were searching for a way of programming - in this case using closed instruction sets like Avida's (another deep topic) - that would be inherently robust to problems like seg faults and illegal instructions.... e.g. Adami's instruction set was engineered so that little programs (creatures) couldn't crash the Avida VM when they mutated into new, unknown programs.. or in Windoze's case, when a coder did something stoopid. It's funny that MS was researching this, since releatively low-tech solutions such as protected memory and QA take care of this. (not to mention Java ;)
  • by PotatoHead ( 12771 ) <doug.opengeek@org> on Thursday May 08, 2003 @11:19AM (#5910358) Homepage Journal
    technique that has always made me think.

    I read a magazine article about this a while back. (probably Sci Am.)

    One researcher setup a problem to be solved with an analog circut. The problem was to distinguish between the words yes and no.

    Nobody can explain how the circut that evolved actually works. Like us, there were parts of the circut that seemed redundant or unnecessary. Sort of like the appendix.

    This whole thing makes me wonder just what we don't know that we think we do.

  • had a nice article about this recently (pp. 52-59 of the Feb 2003 issue). They showed evolutionary design examples primarily in the electronics field, and included an E.D. circuit that was an improvement over existing technology.

  • Computer Evolution (Score:3, Insightful)

    by jefu ( 53450 ) on Thursday May 08, 2003 @12:04PM (#5910787) Homepage Journal
    I've worked with various kinds of things related to genetic algorithms and its a wonderful field and very interesting to work in.

    Its wonderful how these things can find odd and interesting solutions to problems in some cases and completely miss them in others.

    One of the things that anyone learns who has tried this kind of method is that you can't hurry things to a result - that you often need to actively intervene to slow the evolutionary march, or even back it up (as in the article) or the system can easily get stuck exploring an area with a local optimimum extensively and miss a better one thats just a ways away.

    Wonderfully fun stuff though and well worth investigating.

  • their simulations show how a short-term backward step in survival strategies can generate innovative advances.

    This isn't really a challenging assertion, and is well discusssed in evolutionary psychological circles. Consider any given genetic setback. In order for the organism suffering this set back not to be disadvantaged, it must develop a mechanism which compensates for the setback at least as much as the organism is disadvantaged. Simple statistics will show that any solution which is at least as good

  • by gol ( 635335 ) on Thursday May 08, 2003 @12:10PM (#5910846)
    having just successfully completed an undergraduate project in which i have used genetic algorithms to achieve full adaptive image compression, i have learnt rather a lot about these curious beasts that is seldom mentioned in modern text. the use of genetic algorithms in a computer does in no way prove or disprove any evloution/anti-evolution argument. these algorithms do not magically evolve new creatures, or new solutions. they just search the solution space in a highly parallel manner, and they surprise people because they come up with solutions they did not consider. the solution is there waiting in solution space - but you can't find it because your brain is not capapble, you don't spend enough time on it... whatever. this is not new, its not intelligent, its not the creation of a new species. think of genetic algorithms as exploiting adaptive characteristics, simple as that, i.e. skin colour changing due to intensity of sunlight. of course... there are fields of research that involve using one class of genetic algorithms to derive the schemata (structure) of another class, but the research has come up with nothing to date.
  • It's alive, IT'S ALIVE!.....damn, it chewed up my paycheck.
  • Those interested in playing with Avida and seeing how evolution can be modeled using computation, thermodynamics, and information theory should get a copy of Cristoph Adami [caltech.edu]'s book, Introduction to Artificial Life [amazon.com]

    I had the fortune to take Dr. Adami's class [caltech.edu] on the subject. It was an eye-opener to say the least. I think I remember more about statistical physics from his brief overview than I do from any other classes I took on the subject.
  • evolution is dumb (Score:2, Interesting)

    by Anonymous Coward
    There is really nothing particularly amazing about evolutionary or genetic algorithms. They just try a bunch of stuff until they find something that works. In general, they are terribly inefficient algorithms.

    The only reason evolution has been able to come up with amazing results like human life is the immense computing capability of the natural world. One gram of hydrogen has 6.02 x 10^23 atoms. Even if you could represent each of those atoms with one bit of information, we are nowhere near being able
  • Evolvo is a cool program which does genetic images: http://sourceforge.net/projects/evolvo/ [sourceforge.net]

    It's based on Karl Sims work, which I saw presented about 10 years ago at SIGGRAPH. His page is at http://www.genarts.com/karl/ [genarts.com]

    I tried implementing something in LISP then C based on Sims' work way back but got stuck; I'm glad evolvo has emerged so I can actually play with it.

  • Where to get Avida (Score:4, Informative)

    by IdahoEv ( 195056 ) on Thursday May 08, 2003 @03:34PM (#5912724) Homepage
    For the record, I'm one of Dr. Adami's grad students in (The Digital Life Lab) at Caltech. Most of the programming is done at our sister lab in Michigan.

    We recently released Avida version 2.0, with a new GUI and complete with god mode where you can inspect and edit the genome of any organism at any point.

    We encourage you to play with Avida yourself. You can get information and a Mac OS X binary at:

    Avida's Hompeage [caltech.edu]. Older versions for linux and windows are available there as well.

    The intrepid can build the current version for OS X or Linux from source, please see Avida's Sourceforge Project [sourceforge.net]. If you want the nice GUI, you'll need QT.

    Other information about Avida, our lab's research, and artificial life in general can be found at:

    The Digital Life Lab Homepage [caltech.edu]

    Our sister lab at MSU, run by Professors Charles Ofria [msu.edu] and Richard Lenski [msu.edu].

    The Int'l Society For Artificial Life [alife.org]

    • To add one more comment to this (from the Michigan lab mentioned above) we'll have a Windows version of the software out "real soon now". Just this past week we've gotten everything compiled under Visual C++, and are hammering out the last few major bugs. We'll put up a beta as soon as its reasonably solid.
  • by drwho ( 4190 ) on Thursday May 08, 2003 @10:40PM (#5915919) Homepage Journal
    A couple of years ago, Richard Formato (WW1RF) released Yagi Genetic Optimizer, the third edition of his software for using genetic algorithms for antenna design. This stuff does really work, and is useful. It's freeware, but for ms-dos, here [vhfcomm.co.uk]

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