Publications

Dual Phase Evolution (DPE) is a widespread natural process in which complex systems adapt and self-organise by switching alternately between two phases: a phase of global interactions and a phase of local interactions. We show that in evolving networks of agents, DPE can give rise to a wide variety of topologies. In particular, it can lead to the spontaneous emergence of stabilising modular structure.

Complex adaptive and evolutionary systems exhibit a sustained diversity, far-from-equilibrium dynamics, and permanent novelty and adaptation in the absence of a global controller. Previous work shows that many such systems can be represented as networks of interacting components. These networks are typified by certain complex topologies. Insights into the processes behind the emergence of complex network structures and into the effects of such structures are necessary for an understanding of properties that characterise adaptive and evolutionary systems.

Dual Phase Evolution (DPE) is a widespread natural process in which networks underlying complex systems adapt and self-organise by switching alternately between two phases: a phase of global interactions and a phase of local interactions. Each phase is characterised by specific global connectivity and interaction patterns. In this talk I present ongoing work on DPE in complex evolutionary systems. I show how DPE processes can give rise to a wide variety of complex network topologies. In particular, this includes the emergence of scale-free degree distributions fixed-size networks, as well as modular structures. I also show how DPE can be responsible to the continuous novelty observed in many natural and artificial evolutionary systems.

This talk is based on a paper about DPE and Self-Organisation in Networks that was published by myself and my colleagues at SEAL'08.

For further information, please refer to a list of DPE-related papers that I co-authored and follow the references.

We describe a process, Dual Phase Evolution (DPE), which is a widespread mechanism by which systems evolve. The process occurs in systems that switch between two phases: a balance phase and a variation phase. In DPE, processes drive systems to settle in a “balance” phase, but external stimuli can flip the system into a temporary “variation” phase, in which rapid change occurs on all scales. The system gradually returns to a new balance phase, often with different structure than formerly. We argue that the system occurs in many natural systems and show how it results from landscape connectivity in both evolution and long-term forest change. We describe how it underlies certain optimization algorithms, and can be implemented to improve the performance of existing optimization methods. Finally, we present simulation experiments that show how DPE may play a role in creating cliques, clusters, modules and other kinds of order within social networks.