Advice needed on CAS
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Hi folks,
It was about a year ago when i first introduced with the term 'complex adaptive systems', and since that time I've learned lots of things about the subject. I also finished my undergrad studies and these days i am going to choose a new university to continue my studies. My field was control engineering and one can consequently conclude I should choose a control engineering master/doctorate program too. But there exists a master program in complex adaptive systems in Chalmers University, Sweden - and I've been admitted to it - that makes decision making for me difficult. I want to know if you guys in FRIAM can dispense me with some advice. I don't know exactly how the future of complex adaptive systems will be. What is your anticipation? Is it going to die out like some other suddenly flourishing areas such as Cybernetics in two decade ago or not? With a master of complex adaptive systems in your pocket and a fair resume how many doctorate or research positions is available to you? Am I able to change gear and enter another department (like economics or sociology) later for doctorate and work on complex adaptive systems there? This is what I want know - to become a researcher in field of for example economics from eyes of complex adaptive systems one should spend his master in economics or in a program like what I mentioned? I also think that there are lots of jobs available in financial market - how is my guess realistic? I've been a member of FRIAM for six months, and this is my first email. It is not what usually one really likes to read but I hope someone reply it. It will help me a lot in making a decision. kind regards, Habib Talavaty. -------------- next part -------------- An HTML attachment was scrubbed... URL: http://redfish.com/pipermail/friam_redfish.com/attachments/20060512/71d1d910/attachment.htm |
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Dear Habib,
I know some people who have done the Masters on Complex Systems at Chalmers, and they were quite happy with it. The advantage of studying complex systems, being interdisciplinary, is that you can apply the learned knowledge in a wide variety of areas. So if you finish a MSc in complex systems, you could apply the knowledge acquired there to Economics, Engineering, Sociology, etc, but not vice versa... Actually there aren't many other MSc in Complex Systems (at least with that title) I know about... Southampton just made one http:// www.ecs.soton.ac.uk/admissions/pg/complexity_science.php and I remember another one in Italy... About continuing for a PhD, I believe it depends more on the student that on the programme s/he takes. For a PhD you need lots of perseverance and self-motivation, and sometimes that can be difficult. After a Master's, those who would like to continue for a PhD usually find their way, in the same subject, or changing fields. You shouldn't worry about that now... I'm afraid I don't have knowledge about the current state of affairs of the financial market... Hope this helps, Carlos Gershenson... Centrum Leo Apostel, Vrije Universiteit Brussel Krijgskundestraat 33. B-1160 Brussels, Belgium http://homepages.vub.ac.be/~cgershen/ ?Tendencies tend to change...? -------------- next part -------------- An HTML attachment was scrubbed... URL: http://redfish.com/pipermail/friam_redfish.com/attachments/20060512/ef63b248/attachment.htm |
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Hi Carlos, nice to meet you here. I have read some of your papers and have a question: Mamei et al. say in their article about "Case Studies for Self-Organization in Computer Science" http://www.agentgroup.unimo.it/Zambonelli/PDF/JSA.pdf that "Selforganization appears to be the next 'big concept' in science in general". I doubt this is true. Would you agree? According to my experience, dealing with self-organization and "emergence" can be quite frustrating, because they are IMHO more the exception than the rule. They are interesting concepts, but one reason why they are interesting is that they are rare in daily life. Nothing organizes itself or appears out of nowhere. Moreover, there is a natural contradiction between self-organization and engineering: a self-organizing system with emergent properties is not only hard to find, it is obviously hard to design and to engineer. What is your own experience from your work towards a PhD thesis in this area ? Best regards, Jochen |
Self-organization (was Re: Advice needed on CAS)
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Hi Jochen,
Also nice to meet you here, I've also read some of your papers from the arXiv. > Mamei et al. say in their article > about "Case Studies for Self-Organization in Computer Science" > http://www.agentgroup.unimo.it/Zambonelli/PDF/JSA.pdf > actually I am reading that paper now... just went out online in the Journal of Systems Architecture... > that "Selforganization appears to be the next 'big concept' > in science in general". I doubt this is true. Would you agree? Well, there is a renascent interest in it, e.g. there are workshops being organized on the subject (e.g. http://esoa.altarum.net/ esoa06/ ) (renascent because it was very popular in the 40's and 50's within cybernetics) Personally, I don't think it will be "a big hit" in science, because the concept is very loose... and mainstream science likes hard and crisp concepts. As Ashby argued, you can call any dynamics system self-organizing. In other words, dynamical systems have attractors, and if the observer wants to call that attractor an "organized" state, then you have self- organization, since the dynamics tend to the attractor. So there's a bit of subjectivity always tied to self-organization, and many people don't like that. (Well, I would argue that there's a bit of subjectivity in all sciences, even mathematics, but that's another story...) In this paper http://uk.arxiv.org/abs/nlin.AO/0303020 , we argue that the question is not to see wether a system is self-organizing or not, but when it is useful to speak about it or not... > According to my experience, dealing with self-organization and > "emergence" can be quite frustrating, because they are IMHO more > the exception than the rule. They are interesting concepts, but > one reason why they are interesting is that they are rare in > daily life. Nothing organizes itself or appears out of nowhere. It depends on how you see daily life... As I said before, you can see any system as self-organizing, since it is just a description of your observations. So you can describe any animal, any society, any cell, any computer, any car... any system, as self-organizing. The only question is wether this is a useful description or not... and for our daily lives, it is not. You can see emergence as a change of model, or level of description. So it is not that things come out of nowhere, but the observer can describe the observed as emergent or not... So for example anything you touch has temperature, which its atoms don't have, so you can see temperature as an emergent property. The same for life, cognition, etc... Emergence all around us. What I want to say is that describing something as self-organizing or emergent does not change the thing itself, only our description of it. As for now, when is this useful? It seems that only when the usual ways of describing things run into trouble... The thing is that nowadays things seem to run into trouble more and more often... So if we'll change our way of describing daily things or not, that I don't know... > Moreover, there is a natural contradiction between self-organization > and engineering: a self-organizing system with emergent properties > is not only hard to find, it is obviously hard to design and to > engineer. What is your own experience from your work towards a > PhD thesis in this area ? Well, it is hard because we still don't know how to do it properly... I don't see a contradiction here, because self-organization becomes a very useful concept when you have such a huge problem domain that you cannot exhaust it, or when the problem domain is changing constantly, so a solution needs to be actively sought for. If the problem is closed and well defined, self-organization is a redundant concept. But when the system you are engineering is beyond your full comprehension, in the sense that you cannot tell the system precisely what to do, the only choice is to build a system so that it finds itself what to do... And this works for both cases: when you don't know the solution, or when this changes constantly. If you use a traditional approach, you either will get a simplified solution that will not work, or will get a solution that will be outdated before you can implement it... With our current society, there is a demand for these types of systems, but I don't think that the demand for the "traditional" systems will decrease, so for a few decades at least, I don't see self-organization as being "big"... Hope this satisfied more or less your question... Best regards, Carlos Gershenson... Centrum Leo Apostel, Vrije Universiteit Brussel Krijgskundestraat 33. B-1160 Brussels, Belgium http://homepages.vub.ac.be/~cgershen/ ?Tendencies tend to change...? |
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Of course it is a buzzword and a very broad term. I agree that the term is subjective. What I mean is: the concept is useful to explain some causal relationship only at the border between a system and it's environment, if the system is not too big and still comprehensible. The earth as a whole and the computer are both "self-organizing" systems which consume energy and produce entropy (heat). Yet they are very different, and "self-organization" explains nothing here. The term self-organization in general depends on your view of the system. If you say: here is the system, and there is the environment, and if the environment is not organizing the system, then one can say that the system organizes itself (somehow). I think Ashby argued in his original paper "Principles of the Self-Organizing System" that no machine can be self-organized (in the sense of organizational change from bad or useless forms to good and useful types of organization) unless it is coupled to another machine. His paper was quite critical, and it is remarkable that Ashby as a pioneer in the area of self-organization claims that there's no such thing as self-organization in many cases. And he is right: I recently got a new self-cleaning razor (a Braun 8595 Activator), and it consists of two machines, the razor itself, and a docking station which cleans the razor after the use and charges it up. -J. |
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In reply to this post by Jochen Fromm-3
Hi Carlos,
Thanks a lot for your words. They really helped. Anyhow, there is still a question open in my mind about CAS.. Is it going to die out or not? You know, sometimes I think CAS is only a way to tell us we don't know enough, and we should not loose details, not a systematic approach to solve problems. At this point, it seems CAS is a more a means of observe rather than a means of control. Every new observation is only interesting for a while, and soon have to be substituted with another one. I think an example form a work done here at IPM (Institute for Studies in Theoretical Physics and Mathematics, Tehran, Iran) can illuminate what i try to say: We have a paper in review here that suggests neuronal bursts in thalamus are a emergent property and previously neglected details like calcium ion concentration in active canals will dictate if we observe them in our model or not. This is what one can infer from his knowledge of CAS - but only when you have a in depth understanding of system, you can claim you really qualitatively grasp the meaning of it. I hope my words can covey what i try to say, I d be glad to have your comment Carlos. best regards, Habib |
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Hi Habib,
> Anyhow, there is still a question open in my mind about CAS.. > Is it going to die out or not? I don't think so. First of all, previous fields like cybernetics did not die out, but evolved. So now people who studied (or still study) cybernetics per se, find their way. But more importantly, I think that CAS are different from cybernetics, chaos, etc. They have lots of potential, and they have proven to be useful in lots of areas. Moreover, there are several funding opportunities focussing on CAS (at least in Europe), so if there's funding calling for CAS research, people will follow. CAS also suggest a different way of thinking about the world, but wether this will replace Newtonian paradigms in mainstream science or not, remains to be seen. > You know, sometimes I think CAS is only a way to tell us we don't know > enough, and we should not loose details, not a systematic approach to > solve problems. At this point, it seems CAS is a more a means of > observe rather than a means of control. Every new observation is only > interesting for a while, and soon have to be substituted with another > one. Well, indeed there is yet no "science of complexity", but wether we will reach that, or change our concept of science, I think that understanding of CAS has been increasing steadily, so I don't see it dying out, at least for the next decade. If then we won't be speaking about CAS, it won't be because we've forgotten about them, but because we've found something better, and in any case CAS knowledge will be useful there. > I think an example form a work done here at IPM (Institute for Studies > in Theoretical Physics and Mathematics, Tehran, Iran) can illuminate > what i try to say: We have a paper in review here that suggests > neuronal bursts in thalamus are a emergent property and previously > neglected details like calcium ion concentration in active canals will > dictate if we observe them in our model or not. This is what one can > infer from his knowledge of CAS - but only when you have a in depth > understanding of system, you can claim you really qualitatively grasp > the meaning of it. It depends on your purposes. If describing neuronal bursts as emergent properties increases your understanding of the brain, then it's useful. If not, not... Khodahafez, Carlos Gershenson... Centrum Leo Apostel, Vrije Universiteit Brussel Krijgskundestraat 33. B-1160 Brussels, Belgium http://homepages.vub.ac.be/~cgershen/ ?Tendencies tend to change...? |
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