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The holy grail?
When Weaver defined complex systems he made a very clear distinction between the domain of statistical mechanics and complex systems in that the latter were characterized by interactions. There is a big debate in population ecology which is exactly about the implications of assigning macro-scopic properties to the individual elements. So this is another 'complex' complexifying factor - very interesting to think about the implications of that.
 
Odd term that 'power law'. Since it just describes a log log plot why is it always called a law? Some simple complexity texts seem to see this relationship as an underlying fundamental principle of nature. I see this as very Platonist.
 
David Byrne


From: email list for Radical Statistics on behalf of Wells, Julian
Sent: Thu 8/16/2007 5:38 PM
To: [log in to unmask]
Subject: Re: The holy grail?

A point worth making is that in the ideal gas laws as derived in classical statistical mechanics it’s assumed, among other things, that the particles don’t have any relevant macroscopic properties such as size or weight.

 

This assumption is obviously rather debatable in some of the proposed applications (e.g. traffic jams). However, there is work in progress on so-called granular gases (both theoretical and experimental – some people have fun with agitating frames containing a layer of ball-bearings (i.e. 2-D gas) …

 

The following link (found by Googling "granular gases" + "stable distribution") looks like a good starting point for beginners

 

            http://theses.ulb.ac.be/ETD-db/collection/available/ULBetd-10172005-120819/unrestricted/thesis.pdf

 

An inexpert skim of some of this suggests that power-law tails and distributions from the stable family characterise these far-from-equilibrium systems (the equilibrium position of a “gas” of heavy ball-bearings is clearly a heap, not a cloud).

 

Best wishes,

 

Julian

 

 

 

 

 


From: email list for Radical Statistics [mailto:[log in to unmask]] On Behalf Of BYRNE D.S.
Sent: 16 August 2007 15:05
To: [log in to unmask]
Subject: Re: [RADSTATS] The holy grail?

 

This is all about simple complexity and may or may not be correct in relation to such simple complex systems. By a simple complex system I mean a system where emergence occurs solely as a result of interaction among the elements of the system. So for example if we look at a flock of starlings changes in flight pattern result from each bird observing very simple rules in relation to its neighbours but the whole flock generally makes quite complex changes of direction as one, although even here groups may split off. Another example is traffic jams, and Gawd help us all, perhaps financial markets.

 

The key issue would be identifying when a phase shift is about to occur. If there is a constant monitoring of information, or of course in reality a lot of repeated observations, across large numbers of cases, then we might see that point BUT that would seem to destroy the object of the whole exercise since we have to look at lots of cases to know when we can derive information from a few cases.   Financial markets might be an example because aggregate data is generated and can be tracked so monitoring some cases might be enough BUT since the cases would be human subjects as market makers the monitoring might change their behaviour.

 

Crowds are another matter and again how would you monitor - CCTV I suppose. So expect to have the  polises charge you on a demonstration because five people are moving  so as to trigger a response -  recipe for revolution perhaps?

 

David Byrne

 


From: email list for Radical Statistics on behalf of Paul Spicker
Sent: Mon 8/13/2007 1:12 PM
To: [log in to unmask]
Subject: The holy grail?

There is a remarkable claim in the "news" section of New Scientist this week, in a piece entitled "Predicting change, not a moment too soon".  A piece in Physical Review E (which I don't have access to: ref DOI: 10.1103/PhysRevE.75.051125) claims that changes in the behaviour of swarms, crowds, traffic jams or similar systems can be predicted by monitoring a very small number of particles.  "Using a mathematical model of a phase transition, they attempted to detect an oncoming change by monitoring only a small fraction of the elements in the system. They found that they could do so by focusing on the 'mutual information' shared by those elements. ...In a disordered state, looking at a particle gives no information about what others are doing.  As the system approaches a phase transformation, the mutual information betwen particles increases, so that one particle's behaviour does provide information about the speed and trajectory of other particles. ... The researcher's simulations suggest that in a crowd of, say, 1000 people, observations on as few as five people might be sufficient." 

I think it was George Gallup who suggested that it might be ultimately be possible to predict election results using five people. I'm not, sure, though, that I believe it.  If anyone's in a position to appraise the technique it would be fascinating to know about it.

Paul Spicker





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