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Dual phase evolution (DPE) is a process that drives self-organization within complex adaptive systems. It arises in response to phase changes within the network of connections formed by a system's components. DPE occurs in a wide range of physical, biological and social systems. 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 drives self-organization within complex adaptive systems. It arises in response to phase changes within the network of connections formed by a system's components. DPE occurs in a wide range of physical, biological and social systems. Its applications to technology include methods for manufacturing novel materials and algorithms to solve complex problems in computation.

<font color="#ff8000" data-darkreader-inline-color="" style="--darkreader-inline-color:#d2ad7d;">Dual phase evolution 双相演化</font>（DPE）是一个在复杂自适应系统中驱动自组织的过程。它的产生是对系统组成部分所形成的连接网络中的相位变化的响应。DPE发生在广泛的物理、生物和社会系统中。它在技术上的应用包括制造新材料的方法和解决复杂计算问题的算法。

<font color="#ff8000" data-darkreader-inline-color="" style="--darkreader-inline-color:#f9942c;">Dual phase evolution 双相演化</font>（DPE）是一个在复杂自适应系统中驱动自组织的过程。它的产生是对系统组成部分所形成的连接网络中的相位变化的响应。DPE发生在广泛的物理、生物和社会系统中。它在技术上的应用包括制造新材料的方法和解决复杂计算问题的算法。

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Social networks provide a familiar example. In a [[social network]] the nodes of the network are people and the network connections (edges) are relationships or interactions between people. For any individual, social activity alternates between a ''local phase'', in which they interact only with people they already know, and a ''global phase'' in which they can interact with a wide pool of people not previously known to them. Historically, these phases have been forced on people by constraints of time and space. 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. Different processes dominate each phase. Essentially, people make new social links when in the global phase, and refine or break them (by ceasing contact) while in the local phase.

Social networks provide a familiar example. In a [[social network]] the nodes of the network are people and the network connections (edges) are relationships or interactions between people. For any individual, social activity alternates between a ''local phase'', in which they interact only with people they already know, and a ''global phase'' in which they can interact with a wide pool of people not previously known to them. Historically, these phases have been forced on people by constraints of time and space. 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. Different processes dominate each phase. Essentially, people make new social links when in the global phase, and refine or break them (by ceasing contact) while in the local phase.

社交网络提供了一个熟悉的例子。在[[社交网络]]中，网络的节点是人，网络连接（边缘）是人与人之间的关系或互动。对于任何个人来说，社会活动都是在“局部阶段”和“全局阶段”之间交替进行的，在前者中个体只与他们已经认识的人进行互动，在后者中可以与他们以前不认识的大量人进行互动。历史上，这些阶段是由于时间和空间的限制而强加给人们的。人们把大部分时间花在局部阶段，只与周围的人（家人、邻居、同事）交流。然而，诸如聚会、假日和会议之类的间歇式活动涉及到一个全局阶段的转变，在这个阶段，他们可以与不认识的不同的人进行互动。不同的过程控制着每个阶段。从本质上讲，人们在全局阶段建立新的社会联系，在局部阶段则通过停止联系来改善或打破这种联系。  

社交网络提供了一个熟悉的例子。在[[社交网络]]中，网络的节点是人，网络连接（边缘）是人与人之间的关系或互动。对于任何个人来说，社会活动都是在“局部阶段”和“全局阶段”之间交替进行的，在前者中个体只与他们已经认识的人进行互动，在后者中可以与他们以前不认识的大量人进行互动。历史上，这些阶段是由于时间和空间的限制而强加给人们的。人们把大部分时间花在局部阶段，只与周围的人（家人、邻居、同事）交流。然而，诸如聚会、假日和会议之类的间歇式活动涉及到一个全局阶段的转变，在这个阶段，他们可以与不认识的不同的人进行互动。不同的过程控制着每个阶段。从本质上讲，人们在全局阶段建立新的社会联系，在局部阶段则通过停止联系来改善或打破这种联系。  

DPE models of socio-economics interpret the economy as networks of economic agents. Several studies have examined the way socioeconomics evolve when DPE acts on different parts of the network. One model interpreted society as a network of occupations with inhabitants matched to those occupations. In this model social dynamics become a process of DPE within the network, with regular transitions between a development phase, during which the network settles into an equilibrium state, and a mutating phase, during which the network is transformed in random ways by the creation of new occupations.

DPE models of socio-economics interpret the economy as networks of economic agents. Several studies have examined the way socioeconomics evolve when DPE acts on different parts of the network. One model interpreted society as a network of occupations with inhabitants matched to those occupations. In this model social dynamics become a process of DPE within the network, with regular transitions between a development phase, during which the network settles into an equilibrium state, and a mutating phase, during which the network is transformed in random ways by the creation of new occupations.

In a forest, the landscape can be regarded as a network of sites where trees might grow. Some sites are occupied by living trees; others sites are empty. In the local phase, sites free of trees are few and they are surrounded by forest, so the network of free sites is fragmented. In competition for these free sites, local seed sources have a massive advantage, and seeds from distant trees are virtually excluded. Even if a few isolated trees do find free ground, their population is prevented from expanding by established populations, even if the invaders are better adapted to the local environment. 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.

In a forest, the landscape can be regarded as a network of sites where trees might grow. Some sites are occupied by living trees; others sites are empty. In the local phase, sites free of trees are few and they are surrounded by forest, so the network of free sites is fragmented. In competition for these free sites, local seed sources have a massive advantage, and seeds from distant trees are virtually excluded. Even if a few isolated trees do find free ground, their population is prevented from expanding by established populations, even if the invaders are better adapted to the local environment. 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.

DPE occurs where a system has an underlying network. That is, the system's components form a set of nodes and there are connections (edges) that join them. 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 nodes in the network can take physical form, such as atoms held together by atomic forces, or they may be dynamic states or conditions, such as positions on a chess board with moves by the players defining the edges.

DPE occurs where a system has an underlying network. That is, the system's components form a set of nodes and there are connections (edges) that join them. 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 nodes in the network can take physical form, such as atoms held together by atomic forces, or they may be dynamic states or conditions, such as positions on a chess board with moves by the players defining the edges.

 

 

This dual phase process in the landscape explains the consist 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

This dual phase process in the landscape explains the consist 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

 

Graphs and networks have two phases: disconnected (fragmented) and connected. In the connected phase every node is connected by an edge to at least one other node and for any pair of nodes, there is at least one path (sequence of edges) joining them.

Graphs and networks have two phases: disconnected (fragmented) and connected. In the connected phase every node is connected by an edge to at least one other node and for any pair of nodes, there is at least one path (sequence of edges) joining them.

图和网络有两个阶段：断开（碎片化）和连接。在连接阶段，每个节点通过一条边连接到至少一个其他节点，对于任何一对节点，至少有一条路径（边序列）连接它们

图和网络有两个阶段：断开（碎片化）和连接。在连接阶段，每个节点通过一条边连接到至少一个其他节点，对于任何一对节点，至少有一条路径（边序列）连接它们

Problems such as optimization can typically be interpreted as finding the tallest peak (optimum) within a search space of possibilities. The task can be approached in two ways: local search (e.g. hill climbing) involves tracing a path from point to point, and always moving "uphill". Global search involves sampling at wide-ranging points in the search space to find high points.

Problems such as optimization can typically be interpreted as finding the tallest peak (optimum) within a search space of possibilities. The task can be approached in two ways: local search (e.g. hill climbing) involves tracing a path from point to point, and always moving "uphill". Global search involves sampling at wide-ranging points in the search space to find high points.

The [[Erdős–Rényi model]] shows that random graphs undergo a connectivity avalanche as the density of edges in a graph increases.<ref name="Erdos1960">

The [[Erdős–Rényi model]] shows that random graphs undergo a connectivity avalanche as the density of edges in a graph increases.<refname="Erdos1960">

[[Erdős–Rényi模型]]表明，随着图中边密度的增加，随机图会经历连接性雪崩。

[[Erdős–Rényi模型]]表明，随着图中边密度的增加，随机图会经历连接性雪崩。

Many search algorithms involve a transition between phases of global search and local search. 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. Many other nature-inspired algorithms adopt similar approaches. Simulated annealing achieves a transition between phases via its cooling schedule. 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.

Many search algorithms involve a transition between phases of global search and local search. 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. Many other nature-inspired algorithms adopt similar approaches. Simulated annealing achieves a transition between phases via its cooling schedule. 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.