The concept of emergence evolved to capture our intuition that when a large number
of entities interact, the resulting system can display features and behaviours which are
not displayed by the individual constituents. The human body possesses behaviours
and functions which are not expressed by our individual cells; metals show properties
not displayed by individual atoms; societies undergo dynamics which transcend individuals.
Despite a vast literature, going back several decades, no agreement can be found
on a definition, nor on a framework for its study, nor on whether emergence is a 'real'
natural phenomenon or merely a by-product of our perception, or a convenient way to
make sense of processes otherwise too hard to comprehend.
Why should a process which appears so widespread, obvious and at times even easy to model prove so hard to define and conceptualise?
The fundamental reason is that in an emergent process it
is very hard to discriminate 'who does what'. When I decide to listen to music, is it
my 'emergent' self which takes the decision or my cells? My body depends on cellular activity for its functioning, so cells must be the controlling entities. However, no cell
decides to listen to music since listening to music is not something cells 'do'. This leads straight into old and unsolved philosophical problems of causality, determinism and freewill.
Crucially, this is also a technological problem. Today, probably for the first time in history, technological developments in many applications depend on the understanding of emergent phenomena. Advances in Information Technology, Epidemiology, Ecosystem Management, Health Science, just to name a few, depend on approaches which go beyond traditional reductionism and address the understanding of how emergent properties arise, what they 'do' and how they can be controlled.
Despite the philosophical halo of the above discussion, the aim of our research is utterly practical. In a scientific culture in which understanding is increasingly synonymous with computer modelling, we ask what forms of emergence can be studied by simulation and what we can gain from doing so. We will see that computational and 'causal' barriers are strongly related. This may lead to new insights into the limitations and future of the computer modelling of complex processes.
- Boschetti F. & Symons J, 2011, Novel properties generated by interacting computational systems: A minimal model, Complex Systems, 20(2).
- Boschetti F.& Gray R. 2007, A Turing test for Emergence, in M. Prokopenko (ed.), Advances in Applied Self-organizing Systems, Springer-Verlag, London, UK, 2007 , pp 349-364.
- Boschetti F., McDonald D., & Gray, R., 2008, Complexity of a modelling exercise: a discussion of the role of computer simulation in Complex System Science, Complexity, 13(6), pp 21-28.
- Boschetti F., 2010, Causality, emergence, computation and unreasonable expectations, Synthese, 181, 405–412, 10.1007/s11229-010-9720-8.
- Prokopenko M, F.Boschetti, and Ryan A, 2009, An Information-Theoretic Primer On Complexity, Self-Organisation And Emergence, Complexity, DOI: 10.1002/cplx.20249.
- Boschetti F. & Gray R., 2007, Emergence and Computability, Emergence: Complexity and Organization, Volume 9 Issues 1-2, 120-130.
- Boschetti F, Prokopenko M, Macreadie I, Grisogono A. Defining and detecting emergence in complex networks, Conference paper, In R. Khosla, R. J. Howlett, and L. C. Jain, editors, Knowledge-Based Intelligent Information and Engineering Systems, 9th International Conference, KES 2005, Melbourne, Australia, September 14-16, 2005, Proceedings, Part IV, volume 3684 of Lecture Notes in Computer Science, pages 573-580, 2005.
- Batten, D., Boschetti, F., Grisogono AM., & Ryan, A., 2008, Demystifying Emergence, International School on Complexity 9th Course: Emergence in Physical and Biological Systems - Erice 12-16 April 2008.(a quick summary of an old Interaction Task outcomes).