Using Equation-Free Macroscopic Analysis for Studying Self-Organising Emergent Solutions

Giovanni Samaey, Tom Holvoet, Tom De Wolf
2008 2008 Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems  
When engineering distributed software systems based on self-organising emergent solutions, assessing and understanding the relation between the microscopic dynamics and the resulting macroscopic behaviour is a fundamental issue. In our research, we investigate a systematic approach for understanding the link between microscopic and macroscopic behaviour, based on a numerical analysis technique called Equation-Free Macroscopic Analysis. Instead of deriving a (simplified) macroscopic model,
more » ... on-free methods only assume that such a model exists, and mimic a macroscopic simulation using only appropriately initialised simulations with the complete system. There are two crucial issues in this technique. The first issue is defining a complete set of macroscopic variables that would uniquely characterise the self-organising emergent behaviour in the solution. The second issue is the definition of a suitable initialisation operator, that can create a good initial condition for the complete system, given only the values of the macroscopic variables. In this paper, we propose a bottom-up approach for the selection of macroscopic variables and the related initialisation operator. We show how the equation-free approach can guide simulations to systematically increase understanding of the studied system. To illustrate the approach, we use a data clustering system inspired by termite nest building algorithms.
doi:10.1109/saso.2008.30 dblp:conf/saso/SamaeyHW08 fatcat:nh7yc445yvbppe7kkaown2oc54