Automatic characterization of emergent phenomena in complex systems

• DOI: 10.4024/07mo10a.jbpc.10.01
• Publication Date: 2012-01-26T11:06:41Z
• Authors: Thomas Moncion
• Keywords: [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]; 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology; [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]; [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]; 025; 004; [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]

One of the main characteristics of complex systems is that the interrelations between the entities composing the system are not permanently established but evolve along time. As opposed to complicated systems, the structure of complex systems also evolve in a dynamic organizational process. When studying complex systems, self-organization and emergent phenomena must therefore be taken into account and studied carefully. In this paper, we propose to provide tools in order to automatically detect and characterize the emergent phenomena occurring in agent-based simulations. To this end, we consider the interactions between the entities at the lower level as the main organizational forces that shape the structure of the system at a higher level. These interactions are detected during the simulation and represented as dynamic graphs. Measures can then be made on various properties of the graph so as to detect the occurrence of structuring processes. Groups detection and tracking techniques are then introduced so as to characterize more precisely the exact nature of these processes.