This link has been bookmarked by 6 people . It was first bookmarked on 15 Mar 2008, by Mark Nelson.
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02 Jan 09
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27 Nov 08
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So one line of research is to do specific testable ideas on specific systems. But another line of research is to try to find the fundamental principles that underlie, for example, collective decision-making in biological systems. And what we find remarkable is, when we actually look at the algorithms used by, say, an ant colony, or used by a school of fish, when making collective decisions, at a certain level of description, the types of algorithms they use are also the types of algorithms we now know humans use in the visual system, for example, to make decisions about what we are seeing.
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You have this competition between these sources. You have an interaction between positive feedback, which is the amplification of information—that's the trail-laying behavior—and then you have negative feedback because of course if you just have positive feedback, there is no regulation, there is no homeostasis, you can't create these accurate decisions.
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It is a danger called the reminiscence syndrome. One pattern is reminiscent of another, so we think it is the same mechanism, but of course that is not necessarily the case.
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The interaction length scales is centimeters. The swarms are kilometers long, marching through, and it's the density of insects that causes massive problems. It's an enormous problem—locusts can actually invade up to one-fifth of the Earth's land surface during plague years. The Food and Agriculture Organization of the United Nations estimates they affect the livelihood of one in ten people on the planet.
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So what do you do? Do you rely on your local information, or do you tend to follow that individual? These types of rules, these types of interactions, and these types of passive information transfer mechanisms can be important.
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We have been looking at issues of collective memory, how groups can incur a memory of a state, even though the individuals need have no knowledge of that state.
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Instead of animals moving through, say, space, and interacting with each other in their space, we can then abstract the mathematical tools that we have developed into multi-dimensional concept space.
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This strongly changes people's behavior because of course when you see what other people have been doing, you can have this autocatalysis, this positive feedback. You can tend to buy into that because you have seen other people do it.
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what we need to do now, when we are addressing problems such as how an embryo develops, is try to go beyond these caricatures and start building testable predictive models that allow us to test these properties within natural systems. And to do that we need a better understanding of molecular function.
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we still do not have a good thoughtful understanding of cooperation within societies in terms of the level of selection that is acting upon these societies and how that tends to change the optimization principles that underlie these different behaviors.
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We are constantly looking for areas where we can create a more data-driven science behind the spread of these normative behaviors. Of course religion is one such normative behavior, and one of the questions then that we are beginning to interpret with these sorts of models is, when you have could have a whole suite of different possibilities occurring in the world, why do societies collapse down to relatively narrow dimensions, in terms of what they become opposed on? And how did this occur?
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16 Mar 08
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Daniel RourkeI certainly find that the way we interface with the technology is very important. Because despite the fact I use computers and do simulations and taught myself to program computers, I was a reluctant individual. I first started my Ph.D. in '96—I'm 33—
algorithms edge ants brain consciousness technology computer communication reference science biology evolution huge-entity.com
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