生成科学

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此词条暂由Henry翻译。

文件:Game of life torus 100 100 1500.gif
Interaction between a few simple rules and parameters can produce endless, seemingly unpredictable complexity.

Interaction between a few simple rules and parameters can produce endless, seemingly unpredictable complexity.

几个简单规则和参数之间的交互可以产生无穷无尽的、似乎无法预测的复杂性。


Generative science is an area of research that explores the natural world and its complex behaviours. It explores ways "to generate apparently unanticipated and infinite behaviour based on deterministic and finite rules and parameters reproducing or resembling the behavior of natural and social phenomena".[1] By modelling such interactions, it can suggest that properties exist in the system that had not been noticed in the real world situation.[2] An example field of study is how unintended consequences arise in social processes.

Generative science is an area of research that explores the natural world and its complex behaviours. It explores ways "to generate apparently unanticipated and infinite behaviour based on deterministic and finite rules and parameters reproducing or resembling the behavior of natural and social phenomena". By modelling such interactions, it can suggest that properties exist in the system that had not been noticed in the real world situation. An example field of study is how unintended consequences arise in social processes.

生成科学是探索自然世界及其复杂行为的研究领域。它探索了“基于再现或类似自然和社会现象行为的确定性和有限性规则和参数,产生明显出乎意料和无限的行为”的方法。通过对这种相互作用进行建模,它可以表明系统中存在着在现实世界中没有注意到的特性。研究领域的一个例子是研究社会过程中如何产生出乎意料的结果。


Generative sciences often explore natural phenomena at several levels of organization.[3][4] Self-organizing natural systems are a central subject, studied both theoretically and by simulation experiments. The study of complex systems in general has been grouped under the heading of "general systems theory", particularly by Ludwig von Bertalanffy, Anatol Rapoport, Ralph Gerard, and Kenneth Boulding.

Generative sciences often explore natural phenomena at several levels of organization. Self-organizing natural systems are a central subject, studied both theoretically and by simulation experiments. The study of complex systems in general has been grouped under the heading of "general systems theory", particularly by Ludwig von Bertalanffy, Anatol Rapoport, Ralph Gerard, and Kenneth Boulding.

生成科学经常在组织的几个层次上探索自然现象。自组织自然系统是一个重要的研究课题,无论是理论研究还是仿真实验都是如此。一般来说,复杂系统的研究被归在“一般系统理论”的课题下,代表人物有路德维希·冯·贝尔塔兰菲、阿纳托尔·拉波波特、拉尔夫·杰拉德和肯尼斯·博尔丁。


These sciences include psychology and cognitive science, cellular automata, generative linguistics, natural language processing, connectionism, self-organization, evolutionary biology, neural network, social network, neuromusicology, quantum cellular automata, information theory, systems theory, genetic algorithms, computational sociology, communication networks, artificial life, chaos theory, complexity theory, network science, epistemology, quantum dot cellular automaton, quantum computer, systems thinking, genetics, economy, philosophy of science, quantum mechanics, cybernetics, digital physics, digital philosophy, bioinformatics, agent-based modeling and catastrophe theory.

These sciences include psychology and cognitive science, cellular automata, generative linguistics, natural language processing, connectionism, self-organization, evolutionary biology, neural network, social network, neuromusicology, quantum cellular automata, information theory, systems theory, genetic algorithms, computational sociology, communication networks, artificial life, chaos theory, complexity theory, network science, epistemology, quantum dot cellular automaton, quantum computer, systems thinking, genetics, economy, philosophy of science, quantum mechanics, cybernetics, digital physics, digital philosophy, bioinformatics, agent-based modeling and catastrophe theory.

这些科学包括心理学和认知科学、细胞自动机、生成语言学、自然语言处理、连接主义、自我组织、进化生物学、神经网络、社会网络、神经音乐学、量子细胞自动机、信息论、系统论、遗传算法、计算社会学、通信网络、人工生命、混沌理论、复杂性理论、网络科学、认识论、量子点细胞自动机、量子计算机、系统思维、遗传学、经济学、科学哲学、量子力学、控制论、数字物理学、数字哲学、生物信息学、基于代理的建模和灾难理论。


Scientific and philosophical origins科学哲学渊源

Turbulence in the tip vortex from an airplane wing. Studies of the critical point beyond which a system creates turbulence were important for chaos theory, analyzed for example by the Soviet physicist Lev Landau who developed the Landau-Hopf theory of turbulence. David Ruelle and Floris Takens later predicted, against Landau, that fluid turbulence could develop through a strange attractor, a main concept of chaos theory.

[[Turbulence in the tip vortex from an airplane wing. Studies of the critical point beyond which a system creates turbulence were important for chaos theory, analyzed for example by the Soviet physicist Lev Landau who developed the Landau-Hopf theory of turbulence. David Ruelle and Floris Takens later predicted, against Landau, that fluid turbulence could develop through a strange attractor, a main concept of chaos theory.]]

飞机机翼顶端涡流中的湍流。关于系统产生湍流的临界点的研究对于混沌理论非常重要,例如,苏联物理学家Lev Landau开发了Landau-Hopf湍流理论。大卫·鲁埃尔和弗洛里斯·塔肯斯后来预言,流体湍流可能通过一个奇怪的吸引子发展,而这个吸引子是混沌理论的主要概念。

Computer simulation of the branching architecture of the dendrites of pyramidal neurons.

[大锥体神经元树突分支结构的计算机模拟]

The natural phenomenon of herd behaviour as in a flock of birds can be modelled artificially using simple rules in individual units, with swarm intelligence rather than any centralized control.

The natural phenomenon of herd behaviour as in a flock of birds can be modelled artificially using simple rules in individual units, with swarm intelligence rather than any centralized control.

群体行为的自然现象,如鸟群中的行为,可以用简单的个体规则,用群体智能而不是任何集中控制来人工模拟。


The development of computers and automata theory laid a technical foundation for the growth of the generative sciences. For example:

The development of computers and automata theory laid a technical foundation for the growth of the generative sciences. For example:

计算机和自动机理论的发展为生殖科学的发展奠定了技术基础。例如:

  • Cellular automata are mathematical representations of simple entities interacting under deterministic rules to manifest complex behaviours. They can be used to model emergent processes of the physical universe, neural cognitive processes and social behavior.[6][7][8][9]
    • Conway's Game of Life is a zero-player game based on cellular automata, meaning that the only input is in setting the initial conditions, and the game is to see how the system evolves.[10]

[Conway's Game of Life]]是一款基于元胞自动机的零人游戏,也就是说,唯一的输入是设置初始条件,游戏就是看系统如何进化

    • In 1996 Joshua M. Epstein and Robert Axtell wrote the book Growing Artificial Societies which proposes a set of automaton rules and a system called Sugarscape which models a population dependent on resources (called sugar).

1996年,约书亚M爱泼斯坦罗伯特·阿克斯泰尔写了一本书《成长中的人工社会》,书中提出了一套自动化规则和一个名为“Sugarscape”的系统,该系统对依赖资源的人口(称为sugar)进行建模

  • Artificial neural networks attempt to solve problems in the same way that the human brain would, although they are still several orders of magnitude less complex than the human brain and closer to the computing power of a worm. Advances in the understanding of the human brain often stimulate new patterns in neural networks.

人工神经网络试图以人脑同样的方式解决问题,尽管它们的复杂程度仍比人脑低几个数量级,更接近蠕虫的计算能力。对人脑的理解的进步经常能够用来刺激生成神经网络的新模式。


One of the most influential advances in the generative sciences as related to cognitive science came from Noam Chomsky's (1957) development of generative grammar, which separated language generation from semantic content, and thereby revealed important questions about human language. It was also in the early 1950s that psychologists at the MIT including Kurt Lewin, Jacob Levy Moreno and Fritz Heider laid the foundations for group dynamics research which later developed into social network analysis.

One of the most influential advances in the generative sciences as related to cognitive science came from Noam Chomsky's (1957) development of generative grammar, which separated language generation from semantic content, and thereby revealed important questions about human language. It was also in the early 1950s that psychologists at the MIT including Kurt Lewin, Jacob Levy Moreno and Fritz Heider laid the foundations for group dynamics research which later developed into social network analysis.

与认知科学相关的生成科学中最具影响力的进展之一来自诺姆·乔斯基(1957)对生成语法的发展,它将语言生成与语义内容分离开来,从而揭示了有关人类语言的重要问题。同样是在20世纪50年代早期,麻省理工学院的心理学家库尔特·勒温、雅各布·利维·莫雷诺和弗里茨·海德为后来发展为社会网络分析的群体动力学研究奠定了基础。

See also参见

生成系统

References参考

  1. Gordana Dodig-Crnkovic; Raffaela Giovagnoli (2013), "Computing Nature – A Network of Networks of Concurrent Information Processes", in Gordana Dodig-Crnkovic; Raffaela Giovagnoli (eds.), Computing nature: Turing centenary perspective, Springer, p. 7, ISBN 978-3-642-37225-4
  2. Ning Nan, Erik W. Johnston, Judith S. Olson (2008), "Unintended consequences of collocation: using agent-based modeling to untangle effects of communication delay and in-group favor", Computational & Mathematical Organization Theory, 14 (2): 57–83, doi:10.1007/s10588-008-9024-4CS1 maint: uses authors parameter (link)
  3. Farre, G. L. (1997). "The Energetic Structure of Observation: A Philosophical Disquisition". American Behavioral Scientist. 40 (6): 717–728. doi:10.1177/0002764297040006004.
  4. J. Schmidhuber. (1997) A computer scientist's view of life, the universe, and everything. Foundations of Computer Science: Potential – Theory – Cognition, Lecture Notes in Computer Science, pages 201–208, Springer
  5. Hermann Cuntz (2010). "PLoS Computational Biology Issue Image | Vol. 6(8) August 2010". PLOS Computational Biology. 6 (8): ev06.ei08. doi:10.1371/image.pcbi.v06.i08.
  6. Kenrick, DT; Li, NP; Butner, J (2003). "Dynamical evolutionary psychology: individual decision rules and emergent social norms". Psychological Review. 110 (1): 3–28. CiteSeerX 10.1.1.526.5218. doi:10.1037/0033-295X.110.1.3. PMID 12529056.
  7. Epstein, Joshua M.; Axtell, Robert L. (1996). Growing Artificial Societies: Social Science From the Bottom Up. Cambridge MA: MIT/Brookings Institution. p. 224. ISBN 978-0-262-55025-3. https://archive.org/details/growingartificia00epst/page/224. 
  8. Nowak A., Vallacher R.R., Tesser A., Borkowski W. (2000), "Society of Self: The emergence of collective properties in self-structure", Psychological Review, 107 (1): 39–61, doi:10.1037/0033-295x.107.1.39, PMID 10687402CS1 maint: uses authors parameter (link)
  9. Epstein J.M. (1999), "Agent Based Computational Models and Generative Social Science", Complexity, 4 (5): 41–60, Bibcode:1999Cmplx...4e..41E, CiteSeerX 10.1.1.353.5950, doi:10.1002/(SICI)1099-0526(199905/06)4:5<41::AID-CPLX9>3.0.CO;2-F
  10. John Conway's Game of Life


External links外部链接

Category:Systems theory

范畴: 系统论


This page was moved from wikipedia:en:Generative science. Its edit history can be viewed at 生成科学/edithistory