Alex Kalloniatis 5th Nov 2014

CS4-20141105-Alex-KalloniatisOn Wednesday 5th October, Alex Kalloniatis, from Defence Science and Technology Organisation, Canberra, Australia, will give the talk:

Networks and synchronisation: mathematical modelling of socio-technical decision making systems

Life Sciences Building (85), room 2207, Highfield Campus, 4pm. All welcome. Refreshments served after the talk.

Abstract: Much of the decision making in structured organisations such as military, business and administrative units is distributed across many individuals, each contributing information that spans the spectrum from simple ‘facts’ about who and what is ‘out there’, to an integrated understanding of what is happening and why, and what will happen in the future – so that future actions can be determined. They also involve a variety of technological systems and displays to facilitate such Situation Awareness and Sense-Making. Such decision making systems may be represented as networks, and the process of making decisions may be represented as the evolution of individual and collective states in time. In this talk I will present my own efforts at encoding such a model in terms of a system of differential equations based on the well known system of synchronising oscillators, the Kuramoto model. I present two adaptations of this model. The first represents two adversary organisations engaging in a competitive process, each seeking to outpace the speed of decision making of the other. The second focuses on a single organisation but structured in the manner of a typical Divisional construct with separate branches performing different organisational functions, operating under different time pressures and cycles. In both cases, rich seemingly unexpected behaviour arises from numerical solution or simulation – there is ’emergence’ – and dynamical regimes lying between order and chaos. I discuss the value of such models in their tractability to explore, for example, optimal network structures, and the scope for expanding such models to find a balance between Levins’ dimensions of Realism, Precision and Generality.

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