Team:ETH Zurich/human/interviews/expert7

From 2014.igem.org

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Emergence is very intensely discussed in the context of complex systems. Another issue that is more and more discussed in the context of complex systems is the issue of reproducibility of certain results or experiments.  
Emergence is very intensely discussed in the context of complex systems. Another issue that is more and more discussed in the context of complex systems is the issue of reproducibility of certain results or experiments.  
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===Why are complex systems most of time not reproducible? Is it due to the subjectivity of the observer that has to be  
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=== Why are complex systems most of time not reproducible? Is it due to the subjectivity of the observer that has to be taken into account? ===
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taken into account? ===
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That is one issue but I think even more basic is the intrinsic instability of complex systems. When you have unstable behavior, what usually happens is that systems search their sample space in such a way that they end up relaxing into stable attractors. But in complex systems, this can take an enormously long time. There are lots of studies which started in 1990s about these super-transients. The behavior of your complex system can remain transient. This means that your complex system does not reach the stationary regime for an extremely long time. Whenever you are still in the transient phase and you try to reproduce something, you fail, because of the instability. If you know a little bit more about your system then you may be able to calculate with certain tools the time that it takes for the system to become stationary and that helps you. Then you can say: “To achieve reproducible results, I have to wait that much time”. But if you don’t have this knowledge, then you are completely lost.  
That is one issue but I think even more basic is the intrinsic instability of complex systems. When you have unstable behavior, what usually happens is that systems search their sample space in such a way that they end up relaxing into stable attractors. But in complex systems, this can take an enormously long time. There are lots of studies which started in 1990s about these super-transients. The behavior of your complex system can remain transient. This means that your complex system does not reach the stationary regime for an extremely long time. Whenever you are still in the transient phase and you try to reproduce something, you fail, because of the instability. If you know a little bit more about your system then you may be able to calculate with certain tools the time that it takes for the system to become stationary and that helps you. Then you can say: “To achieve reproducible results, I have to wait that much time”. But if you don’t have this knowledge, then you are completely lost.  
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Most of the research results we are talking about are a few decades old. Was there an evolution in the field of complexity this past few years or has the research on complexity attained a bottleneck?  
Most of the research results we are talking about are a few decades old. Was there an evolution in the field of complexity this past few years or has the research on complexity attained a bottleneck?  
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I think there was a very decisive point in time in the study of complexity. That was when people could buy for not so much money high-power computing system. The reason is obvious. You cannot analytically solve complex systems in most cases and if you really want to study them, you have to run them in simulation studies. Everything that happened before the late 1970s was more or less heuristic: mathematicians had analyticalexamples for complex systems. Those examples were the simplest ones. After powerful computer came up, everything could be simulated. Then, the whole field exploded.  
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I think there was a very decisive point in time in the study of complexity. That was when people could buy for not so much money high-power computing system. The reason is obvious. You cannot analytically solve complex systems in most cases and if you really want to study them, you have to run them in simulation studies. Everything that happened before the late 1970s was more or less heuristic: mathematicians had analyticalexamples for complex systems. Those examples were the simplest ones. After powerful computer came up, everything could be simulated. Then, the whole field exploded.
===You just talked about simple complex systems. Does an antagonist notion of complexity like simplicity exist?===
===You just talked about simple complex systems. Does an antagonist notion of complexity like simplicity exist?===

Revision as of 08:10, 17 October 2014

iGEM ETH Zurich 2014