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Ants Solve Steiner Problem

Some years back, ID critic Dave Thomas used to tout the power of genetic algorithms for their ability of solve the Steiner Problem, which basically tries to minimize distance of paths that connect nodes on a two-dimensional surface (last I looked, he’s still making this line of criticism – see here). In fact, none of his criticisms hit the mark — the information problem that he claims to resolve in evolutionary terms merely pushes the design problem deeper, as the peer-reviewed research at the Evolutionary Informatics Lab makes clear (go to the publications page there).

Ants solving Steiner ProblemNow here’s an interesting twist: Colonies of ants, when they make tracks from one colony to another minimize path-length and thereby also solve the Steiner Problem (see “Ants Build Cheapest Network“). So what does this mean in evolutionary terms? In ID terms, there’s no problem — ants were designed with various capacities, and this either happens to be one of them or is one acquired through other programmed/designed capacities. On Darwinian evolutionary grounds, however, one would have to say something like the following: ants are the result of a Darwinian evolutionary process that programmed the ants with, presumably, a genetic algorithm that enables them, when put in separate colonies, to trace out paths that resolve the Steiner Problem. In other words, evolution, by some weird self-similarity, embedded an evolutionary program into the neurophysiology of the ants that enables them to solve the Steiner problem (which, presumably, gives these ants a selective advantage).

I trust good Darwinists will take this in without skipping a beat, mumbling something like “evolution sure is amazing” or “natural selection is cleverer than us.” Dispassionate minds might wonder if something deeper is at stake here.

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7 Responses to Ants Solve Steiner Problem

  1. So what does this mean in evolutionary terms? In ID terms, there’s no problem — ants were designed with various capacities, and this either happens to be one of them or is one acquired through other programmed/designed capacities. On Darwinian evolutionary grounds, however, one would have to say something like the following: ants are the result of a Darwinian evolutionary process that programmed the ants with, presumably, a genetic algorithm that enables them, when put in separate colonies, to trace out paths that resolve the Steiner Problem. In other words, evolution, by some weird self-similarity, embedded an evolutionary program into the neurophysiology of the ants that enables them to solve the Steiner problem (which, presumably, gives these ants a selective advantage).

    One ‘problem’ – if you could call it that – that I have with this is that that “Darwinian evolution” is being called on to explain, and what such an explanation would look like under that assumption (if we can even imagine it aptly), ends up looking and sounding remarkably like design anyway.

    “Something deeper at stake” indeed.

  2. I trust good Darwinists will take this in without skipping a beat, mumbling something like “evolution sure is amazing” or “natural selection is cleverer than us.” Dispassionate minds might wonder if something deeper is at stake here.

    “With “evolution,” all things are possible.”

  3. OT;
    Dr. Dembski, ID The Future just did a podcast in response to the ‘Watson’ victory on Jeopardy;

    What Does Artificial Intelligence Mean for Intelligent Design?
    http://www.idthefuture.com/201.....llige.html

    ,,, and I felt the podcast was a bit light as to the strict limits between the creativity of ‘artificial intelligence’, of what computers can do with information, and the creativity of what humans can do with information. Seeing that you and Dr. Marks, and company, have done extensive work in this area, I was hoping you could possibly do a post on this subject so as to alleviate some of the wild speculation concerning artificial intelligence becoming truly conscious.

  4. Coffee time in Toronto, East Virginny:

    “But the supercomputer’s easy lead throughout the game made its mistake all the more puzzling in the Final Jeopardy! round.

    Under the category of “U.S. Cities,” the competitors were asked to name a city with an airport named after a Second World War hero and one after a Second World War battle. While Watson’s human contestants correctly responded with Chicago, the clearly befuddled computer answered: “What is Toronto?????”

    Jeez, you might think. Any fool knows Toronto isn’t a U.S. city. That’s, like, so elementary, dear Watson.”

    Enjoy the IBM squirm afterward. Should be a dance.

  5. This reminds me of the example Dawkins uses in his book “The Greatest No Show On Earth” about supposed evolution of the birds and their flight patterns.

    These creatures not only have amazing abilities to follow each other but they do it in such a controlled way that they actually work together as a unit. A Darwinian evolutionary explanation would seek to simplify these systems into simple instructions that “just happen” to result in a bigger more cumulatively useful pattern. But mathematically there is an infinite number of behaviors that DO NOT take place and thus allow for these systems to function so efficiently. In theory natural selection could and would weed out the useless traits over time- but odds are that it would not be able to produce a system as efficient as what we see in these cases. The best evidence for the insufficiency of the Darwinian mechanism in these cases is that of “necessary” mechanisms of group awareness having evolved in the first place. It is one thing to have creatures that operate in predictable patterns but when you add into the equation an unpredictable environment that requires that the creatures can sense and correct for disturbances in their targeted goals- then what you really have is a super complex system that has experienced a great many, improbable, positive mutations in order to achieve behavioral systems such as these.

    So, then what do we know of that can arrange a large number of totally improbable events and assemble them to work for a and towards a targeted purpose? Intelligence can. Intelligent agency that is.

  6. On Darwinian evolutionary grounds, however, one would have to say something like the following: ants are the result of a Darwinian evolutionary process that programmed the ants with, presumably, a genetic algorithm that enables them, when put in separate colonies, to trace out paths that resolve the Steiner Problem.

    I don’t understand why would it be a GA. I thought the algorithms that ants used were fairly well known.

  7. I hope that Mr Dembski will have the integrity to respond to the very telling criticism of his remarks about ants and the Steiner problem made by the entomologist and specialist in ants Alex Wild at his blog, Myrmecos; criticism that has been seconded by Jerry Coyne at hisd blog, Why Evolution is True. It is not good to mislead people.

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