Complicated systems are everywhere.  Their complexity arises not due to an absence of knowledge of how its underlying parts function individually, but how a multitude of these parts interact collectively, and nonlinearly to produce behaviors or patterns that are useful.  In the field of Epidemiology, an individual-based simulation of its time evolution can reveal the hubs associated with super-spreaders under heterogeneous conditions, and evolutionary computation is used to identify an optimal set of intervention controls, particularly useful for nosocomial infections.  In HIV-1 infection, the nature of cell entry involving conformational change of the gp120 protein and a varying set of co-receptors is highly dependent on the particular viral strain and of immune cell motility within the host lymphatic system.  Mutations in the virus RNA result in drug-resistant strains when drug treatments are prescribed improperly.  A simulation model of these processes and their time evolution can reveal the efficacy of treatment regimes as a function of viral mutations, leading to the development of therapies capable of suppressing the onset of AIDS while minimizing the risk of anti-drug resistance.  The diversity of such biological systems has fundamentally been attributed to Darwinian natural and sexual selection forces.  Simulating and modeling how these forces apply to the mate preferences of Malaysian stalk-eyed flies, provides us with a virtual laboratory for understanding how self-organization, self-preservation and evolution increases complexity in a system.  With today’s computational power of Grids and Multi-core processors as well as algorithms for inductive learning and stochastic optimization, we are in a solid position to facilitate the search for answers to these questions.

The Evolutionary and Complex Systems programme (EvoCom) at the Emerging Research Laboratory of the School of Computer Engineering, Nanyang Technological University was established in 2004 by Dr Tay Joc Cing to investigate the evolution of complex systems. Many collaborators from Europe, Japan, US and local hospitals, the programme have been making steady progress towards elucidating the nature of such complexity. In particular, EvoCom is an associate partner of the Virolab Consortium, and of the Centre for Mathematics and Physics in Life Sciences and Experimental Biology (CoMPLEX) at University College London. The group has won prizes for its work on evolutionary computation, agent-based simulation and modeling and immune-systems based data mining approaches.