David G Green - Collected Quotes

"Although complex systems may vary enormously in their form and function, most share a common underlying pattern: they consist of ensembles of interacting elements. Interactions between elements define the connectivity, which is a universal attribute of complex systems. Despite superficial differences, most complex systems display patterns of connectivity that are essentially similar." (David G Green, "Self-organisation in complex systems", 2000)

"Although it might be intuitively apparent that a system is complex, defining complexity has proved difficult to pin down with numerous definitions on record. As yet there is no agreed theory of complexity. Much of the mathematics is intractable and computer simulation plays a major part." (Terry R J Bossomaier & David G Green, 2000) 

"Although many natural phenomena may result from the interaction of complex entities, the details of the components may be unimportant. In the discussion of neural networks, the individual neuron turns out to be a highly sophisticated biological system. But the collective properties of neurons may be captured by spin-glass models, in which the neuron is simplified to a binary quantity […] " (Terry R J Bossomaier & David G Green, 2000)

"Difficulties arise when the second law is applied to the real world. If entropy must increase, then how is it possible (say) for all the variety of the living world to persist? The usual answer to the above question is that living systems are open systems, not closed, so the law does not apply locally. However this answer is somewhat unsatisfying. In effect all systems are open systems, since everything interacts with its surroundings to some degree." (David G Green, "Self-organisation in complex systems", 2000)

"If entropy must increase, then how is it possible (say) for all the variety of the living world to persist? The usual answer to the above question is that living systems are open systems, not closed, so the law does not apply locally. However this answer is somewhat unsatisfying. In effect all systems are open systems, since everything interacts with its surroundings to some degree." (David G Green, 2000) 

"Interaction: the other major source of complexity is the interaction of many autonomous, adaptive agents. Again, there are many questions to ask about the agents, the nature of the interaction and the circumstances in which complex surface phenomena result." (Terry R J Bossomaier & David G. Green, 2000)

"Iteration: fractals and chaos result from repetition of simple operations. These generating rules produce complex phenomena. There are many interesting questions to ask about how to describe the processes, how to measure the resulting complexity, whether we can work backwards from the reult to the rules and so on. (Terry R J Bossomaier & David G. Green, 2000)

"Networks [...] are usually distinguished from graphs by virtue of the special weightings placed upon either links or nodes or both. Weighted links indicate the strength of the relationship, and signs, when they exist, indicate a direction in a manner similar to directed graphs. Weighted nodes indicate that an entity is measured by some attribute relevant to the study under investigation." (D A Seeley, "Network evolution and the emergence of structure", 2000)

"Of course what we would all like to see is a general theory of complex systems or complexity. Despite several promising candidates the selection process is still under way. Maybe there is no universal theory, but there are certainly common paradigms and methods which have proved to be useful across a wide area." (Terry R J Bossomaier & David G Green, 2000)

"Perhaps the greatest puzzle in self-organisation is the question of emergent properties. That is, how do features that characterise a system as a whole emerge from the interplay of the parts that go to makeup the system? […] The issue of self-organisation remains as great a challenge today as it ever has been. Though there remains much yet to learn about self-organisation, we can at least identify some of the processes involved." (David G Green, "Self-organisation in complex systems", 2000)

"The evident power of simple heuristics […] teaches us the important lesson that global behavior patterns, and social organization, can emerge out of local interactions. Organisms do not necessarily need to have an over-riding plan nor do they require awareness of the large-scale. Grand patterns and processes can emerge as the nett effect of small-scale, local behavior."(David G Green, 2000) 

"The really crucial question in multi-object systems is whether local interactions do grow into large-scale patterns." (David G Green, 2000)

"The second law states that entropy always increases within closed systems. This is really a statement about average behaviour. High entropy means uniformity, differences ('order') are damped by interactions within the system. For water in a tub the water molecules exchange energy via what are essentially elastic collisions. Thus water everywhere in the tub soon acquires the same temperature. What the water does not do is to separate spontaneously into areas of hot and cold water. That would be to decrease the entropy in the system." (David G Green, "Self-organisation in complex systems", 2000)

"The self-similarity on different scales arises because growth often involves iteration of simple, discrete processes (e.g. branching). These repetitive processes can often be summarized as sets of simple rules." (David G Green, 2000)