Dual-phase evolution
Dual phase evolution (DPE) is a process that drives self-organization within complex adaptive systems.
[1] It arises in response to phase changes within the network of connections formed by a system's components.
Its applications to technology include methods for manufacturing novel materials and algorithms to solve complex problems in computation.
Dual phase evolution (DPE) is a process that promotes the emergence of large-scale order in complex systems.
People spend most of their time in a local phase and interact only with those immediately around them (family, neighbors, colleagues).
However, intermittent activities such as parties, holidays, and conferences involve a shift into a global phase where they can interact with different people they do not know.
For example, a family tree is a network in which the nodes are people (with names) and the edges are relationships such as "mother of" or "married to".
The alternation between local and global phases in social networks occurs in many different guises.
Some transitions between phases occur regularly, such as the daily cycle of people moving between home and work.
[5] Several studies have examined the way socioeconomics evolve when DPE acts on different parts of the network.
[1] Major fires (or other disturbances) clear away large tracts of land, so the network of free sites becomes connected and the landscape enters a global phase.
A fire in such conditions leads to an explosion of the invading population, and possibly to a sudden change in the character of the entire forest.
This dual phase process in the landscape explains the consistent appearance of pollen zones in the postglacial forest history of North America, Europe, as well as the suppression of widespread taxa, such as beech and hemlock, followed by huge population explosions.
Similar patterns, pollen zones truncated by fire-induced boundaries, have been recorded in most parts of the world Dual-phases also occur in the course of foraging by animals.
[10] In ant colonies, for instance, individuals search at random (exploration) until food is found.
Problems such as optimization can typically be interpreted as finding the tallest peak (optimum) within a search space of possibilities.
[3] A simple example is the Great Deluge algorithm in which the searcher can move at random across the landscape, but cannot enter low-lying areas that are flooded.
At first the searcher can wander freely, but rising water levels eventually confine the search to a local area.
The cellular genetic algorithm places solutions in a pseudo landscape in which they breed only with local neighbours.
Intermittent disasters clear patches, flipping the system into a global phase until gaps are filled again.
These are related to the Baldwin effect, which arises when processes acting on phenotypes (e.g. learning) influence selection at the level of genotypes.
Dual phase evolution is related to the well-known phenomenon of self-organized criticality (SOC).
Both concern processes in which critical phase changes promote adaptation and organization within a system.
