C&B Notes

Collective Computation

C4, a research group at the Santa Fe Institute, studies all levels of biological organization — from societies of cells to societies of individuals to machine-human hybrid societies — to better understand collective behavior, collective computation, and collective intelligence.  The group has begun recently to extend its efforts into the complex adaptive systems that are financial markets.

Flack describes her work as an investigation into three interlocking questions.  She wants to understand how phenomenological rules in biology, which seem to work in aggregate, emerge from microscopic ground truths.  She wants to understand how groups solve problems and come to decisions.  And she wants to know how complex systems stay robust in the face of shocks, like the macaques with their own police force that acts as social glue.

At its root, though, Flack’s focus is on information: specifically, on how groups of different, error-prone actors variously succeed and fail at processing information together.  “When I look at biological systems, what I see is that they are collective,” she said.  “They are all made up of interacting components with only partly overlapping interests, who are noisy information processors dealing with noisy signals.”

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Q&A with Dr. Flack

Collective computation is about how adaptive systems solve problems.  All systems are about extracting energy and doing work, and physical systems in particular are about that.  When you move to adaptive systems, you’ve got the additional influence of information processing, which we think allows a system to extract energy more efficiently even though it has to expend a little extra energy to do the information processing.  Components of adaptive systems look out at the world, and they try to discover the regularities.  It’s a noisy process…

What we are doing at C4 is taking messy, conceptually challenging problems and turning them into something rigorous.  We’re very philosophically oriented, but we’re also very quantitative, particularly in thinking about how nature can overcome subjectivity in information processing through collective computation.  We really think the answer to these questions requires combining insights from statistical physics, theoretical computer science, information theory, evolutionary biology and cognitive science….

Jorge Luis Borges is one of my favorite writers, and he wrote something along the lines of “the worst labyrinth is not that intricate form that can trap us forever, but a single and precise straight line.”  My path is not a straight line.  It has been a quite interesting, labyrinthine path, and I guess I would say not to be afraid of that.  You don’t know what you’re going to need, what tools or concepts you’re going to need.  The thing is to read broadly and always keep learning…

A lot of the discussion is: “What is the core problem, how do we simplify, what are the right measurements, what are the right variables, what is the right way to represent this problem mathematically?”  It’s always a combination of the data, these discussions, and the math on the board that leads us to a representation of the problem that gives us traction…

We have this argument at the Santa Fe Institute a lot.  Some people will say, “Well, at the end of the day it’s all math.”  And I just don’t believe that.  I believe that science sits at the intersection of these three things — the data, the discussions and the math.  It is that triangulation — that’s what science is.  And true understanding, if there is such a thing, comes only when we can do the translation between these three ways of representing the world.

h/t Chris Pavese

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