复杂适应系统
[复杂适应性系统-复杂/游戏高手、Complex Adaptive System (CAS)]
复杂性科学的研究已经不像以前那样雄心勃勃了，它似乎自我约束在一个领域——复杂适应性系统。【永恒的新奇】计算机科学家约翰.荷兰德（John H．Holland），遗传算法的创始人，成为该研究方向的指引者。【1987年9月他的演讲《作为适应性过程的全球经济》也许是复杂适应性系统研究的最早论述了，近20年这一领域又取得什么有趣的进展,值得进一步了解】因此，CAS几个性质的简单描述：【重点是：如何将这一切应用到自己的研究领域之中去】
每一个CAS都是一个由许多平行发生作用的"作用者"组成的网络。
每一个复杂的适应性系统都具有多层次组织，每一个层次的作用者对更高层次的作用者来说都起着建设砖块的作用。
所有复杂的适应性系统都会预期将来。
复杂的适应性系统总是会有很多小生境，每一个这样的小生境都可以被一个能够使自己适应在其间发展的作用者所利用。
按照这篇What are Complex Adaptive Systems? CAS具有很多的特性，其中最重要的有：
Emergence/涌现: Rather than being planned or controlled the agents in the system interact in apparently random ways. From all these interactions patterns emerge which informs the behavior of the agents within the system and the behavior of the system itself. For example a termite hill is a wondrous piece of architecture with a maze of interconnecting passages, large caverns, ventilation tunnels and much more. Yet there is no grand plan, the hill just emerges as a result of the termites following a few simple local rules.
Co-evolution/共同进化: All systems exist within their own environment and they are also part of that environment. Therefore, as their environment changes they need to change to ensure best fit. But because they are part of their environment, when they change, they change their environment, and as it has changed they need to change again, and so it goes on as a constant process. ( Perhaps it should have been Darwin's "Theory of Co-evolution". )
Some people draw a distinction between complex adaptive systems and complex evolving systems. Where the former continuously adapt to the changes around them but do not learn from the process. And where the latter learn and evolve from each change enabling them to influence their environment, better predict likely changes in the future, and prepare for them accordingly.
Sub optimal/次最优化: A complex adaptive systems does not have to be perfect in order for it to thrive within its environment. It only has to be slightly better than its competitors and any energy used on being better than that is wasted energy. A complex adaptive systems once it has reached the state of being good enough will trade off increased efficiency every time in favour of greater effectiveness.
Requisite Variety/不可缺少的多样性: The greater the variety within the system the stronger it is. In fact ambiguity and paradox abound in complex adaptive systems which use contradictions to create new possibilities to co-evolve with their environment. Democracy is a good example in that its strength is derived from its tolerance and even insistence in a variety of political perspectives.
Connectivity/连通性: The ways in which the agents in a system connect and relate to one another is critical to the survival of the system, because it is from these connections that the patterns are formed and the feedback disseminated. The relationships between the agents are generally more important than the agents themselves.
Simple Rules/简单的规律: Complex adaptive systems are not complicated. The emerging patterns may have a rich variety, but like a kaleidoscope the rules governing the function of the system are quite simple. A classic example is that all the water systems in the world, all the streams, rivers, lakes, oceans, waterfalls etc with their infinite beauty, power and variety are governed by the simple principle that water finds its own level.
Iteration/迭代: Small changes in the initial conditions of the system can have significant effects after they have passed through the emergence - feedback loop a few times (often referred to as the butterfly effect). A rolling snowball for example gains on each roll much more snow than it did on the previous roll and very soon a fist sized snowball becomes a giant one.
Self Organizing/自组织: There is no hierarchy of command and control in a complex adaptive system. There is no planning or managing, but there is a constant re-organizing to find the best fit with the environment. A classic example is that if one were to take any western town and add up all the food in the shops and divide by the number of people in the town there will be near enough two weeks supply of food, but there is no food plan, food manager or any other formal controlling process. The system is continually self organizing through the process of emergence and feedback.
Edge of Chaos/混沌边缘: Complexity theory is not the same as chaos theory, which is derived from mathematics. But chaos does have a place in complexity theory in that systems exist on a spectrum ranging from equilibrium to chaos. A system in equilibrium does not have the internal dynamics to enable it to respond to its environment and will slowly (or quickly) die. A system in chaos ceases to function as a system. The most productive state to be in is at the edge of chaos where there is maximum variety and creativity, leading to new possibilities.
Nested Systems/嵌套的系统: Most systems are nested within other systems and many systems are systems of smaller systems. If we take the example in self organizing above and consider a food shop. The shop is itself a system with its staff, customers, suppliers, and neighbors. It also belongs the food system of that town and the larger food system of that country. It belongs to the retail system locally and nationally and the economy system locally and nationally, and probably many more. Therefore it is part of many different systems most of which are themselves part of other systems.
复杂性科学的研究已经不像以前那样雄心勃勃了，它似乎自我约束在一个领域——复杂适应性系统。【永恒的新奇】计算机科学家约翰.荷兰德（John H．Holland），遗传算法的创始人，成为该研究方向的指引者。【1987年9月他的演讲《作为适应性过程的全球经济》也许是复杂适应性系统研究的最早论述了，近20年这一领域又取得什么有趣的进展,值得进一步了解】因此，CAS几个性质的简单描述：【重点是：如何将这一切应用到自己的研究领域之中去】
每一个CAS都是一个由许多平行发生作用的"作用者"组成的网络。
每一个复杂的适应性系统都具有多层次组织，每一个层次的作用者对更高层次的作用者来说都起着建设砖块的作用。
所有复杂的适应性系统都会预期将来。
复杂的适应性系统总是会有很多小生境，每一个这样的小生境都可以被一个能够使自己适应在其间发展的作用者所利用。
按照这篇What are Complex Adaptive Systems? CAS具有很多的特性，其中最重要的有：
Emergence/涌现: Rather than being planned or controlled the agents in the system interact in apparently random ways. From all these interactions patterns emerge which informs the behavior of the agents within the system and the behavior of the system itself. For example a termite hill is a wondrous piece of architecture with a maze of interconnecting passages, large caverns, ventilation tunnels and much more. Yet there is no grand plan, the hill just emerges as a result of the termites following a few simple local rules.
Co-evolution/共同进化: All systems exist within their own environment and they are also part of that environment. Therefore, as their environment changes they need to change to ensure best fit. But because they are part of their environment, when they change, they change their environment, and as it has changed they need to change again, and so it goes on as a constant process. ( Perhaps it should have been Darwin's "Theory of Co-evolution". )
Some people draw a distinction between complex adaptive systems and complex evolving systems. Where the former continuously adapt to the changes around them but do not learn from the process. And where the latter learn and evolve from each change enabling them to influence their environment, better predict likely changes in the future, and prepare for them accordingly.
Sub optimal/次最优化: A complex adaptive systems does not have to be perfect in order for it to thrive within its environment. It only has to be slightly better than its competitors and any energy used on being better than that is wasted energy. A complex adaptive systems once it has reached the state of being good enough will trade off increased efficiency every time in favour of greater effectiveness.
Requisite Variety/不可缺少的多样性: The greater the variety within the system the stronger it is. In fact ambiguity and paradox abound in complex adaptive systems which use contradictions to create new possibilities to co-evolve with their environment. Democracy is a good example in that its strength is derived from its tolerance and even insistence in a variety of political perspectives.
Connectivity/连通性: The ways in which the agents in a system connect and relate to one another is critical to the survival of the system, because it is from these connections that the patterns are formed and the feedback disseminated. The relationships between the agents are generally more important than the agents themselves.
Simple Rules/简单的规律: Complex adaptive systems are not complicated. The emerging patterns may have a rich variety, but like a kaleidoscope the rules governing the function of the system are quite simple. A classic example is that all the water systems in the world, all the streams, rivers, lakes, oceans, waterfalls etc with their infinite beauty, power and variety are governed by the simple principle that water finds its own level.
Iteration/迭代: Small changes in the initial conditions of the system can have significant effects after they have passed through the emergence - feedback loop a few times (often referred to as the butterfly effect). A rolling snowball for example gains on each roll much more snow than it did on the previous roll and very soon a fist sized snowball becomes a giant one.
Self Organizing/自组织: There is no hierarchy of command and control in a complex adaptive system. There is no planning or managing, but there is a constant re-organizing to find the best fit with the environment. A classic example is that if one were to take any western town and add up all the food in the shops and divide by the number of people in the town there will be near enough two weeks supply of food, but there is no food plan, food manager or any other formal controlling process. The system is continually self organizing through the process of emergence and feedback.
Edge of Chaos/混沌边缘: Complexity theory is not the same as chaos theory, which is derived from mathematics. But chaos does have a place in complexity theory in that systems exist on a spectrum ranging from equilibrium to chaos. A system in equilibrium does not have the internal dynamics to enable it to respond to its environment and will slowly (or quickly) die. A system in chaos ceases to function as a system. The most productive state to be in is at the edge of chaos where there is maximum variety and creativity, leading to new possibilities.
Nested Systems/嵌套的系统: Most systems are nested within other systems and many systems are systems of smaller systems. If we take the example in self organizing above and consider a food shop. The shop is itself a system with its staff, customers, suppliers, and neighbors. It also belongs the food system of that town and the larger food system of that country. It belongs to the retail system locally and nationally and the economy system locally and nationally, and probably many more. Therefore it is part of many different systems most of which are themselves part of other systems.
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