It's always hard to predict the kinds of cross fertilisations that will occur between different areas within the interdisciplinary hot-house of agent-based research. It is now widely established that biologically-inspired mechanisms are applicable as basis for the engineering of distributed and robust systems. For example, many adaptive agent algorithms draw inspiration from biological evolution and there has been much recent work on ant-inspired routing methods to name just two. Here we report on recent developments in which mechanisms derived from social theories, particularly computationally expressed mechanisms through agent-based social simulation, are being applied to tough engineering problems in distributed settings.

The idea of using “social metaphors” for thinking about self-organising software is not new.  Marvin Minsky's classic A.I. Text “Society Of Mind” (Minsky 1988) explicitly envisages minds as composed of semi-autonomous entities with coalitions, conflicts and hierarchies. What is new is the application of techniques from multi-agent-based social simulation (MABS) to the hard distributed engineering problems that agent researchers are interested in today.

For well over a decade simulation-friendly social scientists have been using multi-agent-based simulations to develop, test and communicate mechanisms of social emergence. This means programming individual agents with (often sophisticated) individual behavioural and learning rules and then executing simulations to determine what kinds of societies and structures emerge. The focus of much of this research has been on trying to gain a greater understanding of human societies – the world we actually live in. However, some of the mechanisms that have been discovered are directly relevant to open engineering issues in distributed systems

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