Publications

Understanding the origins of complexity is a key challenge in many sciences. Although networks are known to underlie most systems, showing how they contribute to well-known phenomena remains an issue. Here, we show that recurrent phase transitions in network connectivity underlie emergent phenomena in many systems. We identify properties that are typical of systems in different connectivity phases, as well as characteristics commonly associated with the phase transitions. We synthesize these common features into a common framework, which we term dual-phase evolution (DPE). Using this framework, we review the literature from several disciplines to show that recurrent connectivity phase transitions underlie the complex properties of many biological, physical and human systems. We argue that the DPE framework helps to explain many complex phenomena, including perpetual novelty, modularity, scale-free networks and criticality. Our review concludes with a discussion of the way DPE relates to other frameworks, in particular, self-organized criticality and the adaptive cycle.

This is a republication of this 2009 paper.

Evidence from several fields suggests that dual phase evolution (DPE) may account for distinctive features associated with complex adaptive systems. Here, we review empirical and theoretical evidence for DPE in natural systems and examine the relationship of DPE to self-organized criticality and adaptive cycles. A general model for DPE in networks is outlined, with preliminary data illustrating the emergence of phase changes.

Evidence from several fields suggests that Dual Phase Evolution (DPE) may account for distinctive features associated with complex adaptive systems. We review empirical and theoretical evidence for DPE in natural systems and examine the relationship of DPE to other complexity theories such self-organised criticality and adaptive cycles.

Evidence from several fields suggests that dual phase evolution (DPE) may account for distinctive features associated with complex adaptive systems. Here, we review empirical and theoretical evidence for DPE in natural systems and examine the relationship of DPE to self-organized criticality and adaptive cycles. A general model for DPE in networks is outlined, with preliminary data illustrating the emergence of phase changes.

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.

In this study, we describe an evolutionary mechanism – Dual Phase Evolution (DPE) – and argue that it plays a key role in the emergence of internal structure in complex adaptive systems (CAS). Our DPE theory proposes that CAS exhibit two well-defined phases – selection and variation – and that shifts from one phase to the other are triggered by external perturbations. We discuss empirical data which demonstrates that DPE processes play a prominent role in species evolution within landscapes and argue that processes governing a wide range of self-organising phenomena are similar in nature. In support, we present a simulation model of adaptive radiation in landscapes. In the model, organisms normally exist within a connected landscape in which selection maintains them in a stable state. Intermittent disturbances (such as fires, commentary impacts) flip the system into a disconnected phase, in which populations become fragmented, freeing up areas of empty space in which selection pressure lessens and genetic variation predominates. The simulation results show that the DPE mechanism may indeed facilitate the appearance of complex diversity in a landscape ecosystem.

Recent studies suggest that macro-evolutionary patterns such as punctuated equilibrium may be generated by a process termed Dual Phase Evolution (DPE). According to the DPE hypothesis, evolution in landscapes exhibits two phases – selection and variation. Disturbances such as mass extinctions can flip the landscape from selection to variation phases. Similar processes occur in a wide range of artificial, natural and social complex systems. Here, we show that mass extinctions induce DPE in a simulation model of adaptive radiation. The model is based on a previous model of adaptive radiation which did not incorporate Dual Phase Evolution. Results confirm that mass extinctions caused by external disturbances can trigger periods of rapid species turnover and adaptive radiation (variation phases), which are followed by long periods without innovation (selection phases). Our simulations also show that the spatial configuration of disasters leading to mass extinctions strongly influences whether and to what extent such disasters are capable of inducing evolutionary variation phases.

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.