“糖域模型”的版本间的差异

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===Mathematica===
 
===Mathematica===
Another implementation can be found written in [[Mathematica]].<ref>{{cite web
+
也可以在Mathematica上实现。<ref>{{cite web
 
|url=http://demonstrations.wolfram.com/SugarscapeAgentBasedModeling/
 
|url=http://demonstrations.wolfram.com/SugarscapeAgentBasedModeling/
 
|title=Sugarscape: Agent-Based Modeling<!--sic--> - Wolfram Demonstrations Project
 
|title=Sugarscape: Agent-Based Modeling<!--sic--> - Wolfram Demonstrations Project

2020年11月12日 (四) 18:12的版本


糖域模型是一个遵循一些简单规则的多主体模型,用于人工智能基于主体建模以及社会仿真等领域,在Joshua M. Epstein和Robert Axtell一起出版的书籍中《不断发展的人工社会》Growing Artificial Societies中有介绍。[1]

起源

Fundaments of Sugarscape models can be traced back to the University of Maryland where economist Thomas Schelling presented his paper titled Models of Segregation. Written in 1969, Schelling and the rest of the social environment modelling fraternity had their options limited by a lack of adequate computing power and an applicable programming mechanism to fully develop the potential of their model.

糖域模型的基础可以追溯到马里兰大学 University of Maryland的经济学家托马斯·谢林 Thomas Schelling 在他的论文提出的谢林的种族隔离模型 Schelling's model of segregation[2]。这篇论文写于1969年,由于缺乏足够的计算能力和适合的编程机制,从而导致没有充分挖掘出他们模型的潜力。


John Conway's agent-based simulation "Game of Life" was enhanced and applied to Schelling's original idea by Joshua M. Epstein and Robert Axtell in their book Growing Artificial Societies. To demonstrate their findings on the field of agent-based simulation, a model was created and distributed with their book on CD-ROM. The concept of this model has come to be known as "the Sugarscape model".[1] Since then, the name "Sugarscape" has been used for agent-based models using rules similar to those defined by Epstein & Axtell.

Joshua M. Epstein和Robert Axtell在他们的书中,应用了约翰·何顿·康威 John Horton Conway提出来的基于主题的模拟的一个模型,叫做生命游戏,并将其应用于谢林的最初的想法中。为了证明他们在基于代理的仿真领域的发现,创建了一个模型并将其与CD-ROM上的书一起分发。这个模型就是我们现在众所周知的概念”糖域模型“[1] 。此后,糖域模型就被广泛使用于基于主体的模型中,只要这些模型使用的规则与Epstein&Axtell定义的规则相似,都可以被称作是”糖域模型“。

原理

All Sugarscape models include the agents (inhabitants), the environment (a two-dimensional grid) and the rules governing the interaction of the agents with each other and the environment.

所有的糖域模型都包括主体(居民),环境(二维网格)以及控制主体之间,主体和环境之间相互作用的规则。


The original model presented by J. Epstein & R. Axtell (considered as the first large scale agent model) is based on a 51x51 cell grid, where every cell can contain different amounts of sugar (or spice). In every step agents look around, find the closest cell filled with sugar, move and metabolize. They can leave pollution, die, reproduce, inherit sources, transfer information, trade or borrow sugar, generate immunity or transmit diseases - depending on the specific scenario and variables defined at the set-up of the model.

J. Epstein&R. Axtell最初提出来的模型(被认为是第一个大规模社会仿真的主体模型),这个模型是基于51x51的细胞网格,其中每个细胞可以包含不同量的糖(或香料)。在每个步骤中,主体都会环顾四周,找到离自己最近的充满糖的细胞网格,然后移动并代谢。它们可能会留下污染,死亡,繁殖,继承资源,传递信息,交易或借糖,产生免疫力或传播疾病-取决于模型设置时定义的特定情况和变量。

Sugar in simulation could be seen as a metaphor for resources in an artificial world through which the examiner can study the effects of social dynamics such as evolution, marital status and inheritance on populations.

模拟中的”糖“可以看作是人造世界中资源的隐喻,设计者可以通过该隐喻来研究诸如进化,婚姻状况和继承等社会动态对人口的影响。[3]


J. Epstein和R. Axtell在他们的书中提供的原始规则的精确模拟可能会出现问题[4],因为并不总是能够复现出《发展中的人工社会》中提供的结果。


Exact simulation of the original rules provided by J. Epstein & R. Axtell in their book can be problematic and it is not always possible to recreate the same results as those presented in Growing Artificial Societies.

模型实现

The Sugarscape model has had several implementations, some of which are available as open source software. 糖域模型已经有多种实现方式,其中一些可以在开源软件中获得。


Ascape

An original implementation was developed in Ascape, Java software suitable for agent-based social simulation. The Sugarscape model remains part of the built-in library of models distributed with Ascape.[5] 一个最初的应用实现是基于Ascape开发的。Java软件适合做基于主体的社会仿真。糖域模型仍然是Ascape内嵌库模型中的一部分。

NetLogo has been used to build Sugarscape models. Three Sugarscape scenarios are included in the NetLogo Models Library: "Immediate Growback", "Constant Growback" and "Wealth Distribution". Besides these three scenarios lies Iain Weaver's Sugarscape NetLogo model, which is part of the User Community Models Library. "It builds on Owen Densmore's NetLogo community model to encompass all rules discussed in Growing Artificial Societies with the exception of the combat rule (although trivial to include, it adds little value to the model)."[6] The model is equipped with rich documentation[7] including instructions for successful replication of the original Sugarscape rules.[4]

NetLogo已经可以实现Sugarscape模型。NetLogo模型库中包含三个Sugarscape场景:“立即回升”,“恒定回升”和“财富分配”。除了这三种方案外,还有Iain Weaver的Sugarscape NetLogo模型,该模型是用户社区模型库的一部分。“它建立在Owen Densmore的NetLogo社区模型的基础上,涵盖了除战斗规则(尽管包含了琐碎的规则,但对模型却没有多大价值)之外的发展中的人工社会中讨论的所有规则。” [6]该模型配备了丰富的文档[7],其中包括成功复制原始Sugarscape规则的说明。[4]



SugarScape on steroids

Due to the emergent nature of agent-based models (ABMs), it is critical that the population sizes in the simulations match the population sizes of the dynamic systems being modelled.[8] However, the performance of contemporary agent simulation frameworks has been inadequate to handle such large population sizes and parallel computing frameworks designed to run on computing clusters has been limited by available bandwidth. As computing power increases with Moore's law, the size and complexity of simulation frameworks can be expected to increase. The team of R. M. D’Souza, M. Lysenko and K Rahmani from Michigan Technological University used a Sugarscape model to demonstrate the power of Graphics processing units (GPU) in ABM simulations with over 50 updates per second with agent populations exceeding 2 million.[9]

Mathematica

也可以在Mathematica上实现。[10]

MASON

GMU's MASON project, available under the Academic Free License, also includes an implementation of Sugarscape.[11]

References

  1. 1.0 1.1 1.2 Epstein, Joshua M.; Axtell, Robert (October 11, 1996). Growing artificial societies: social science from the bottom up. Brookings Institution Press. pp. 224. ISBN 978-0-262-55025-3. https://archive.org/details/growingartificia00epst/page/224. 
  2. "Sugarscape - Growing Agent-based Artificial Societies". Sourceforge. Retrieved 7 November 2010.
  3. "Agents at Work". CIO Insight. 1 (27): 43. 1 June 2003. ISSN 1535-0096. Retrieved November 11, 2010.(Retrieved from ABI/Inform Document ID: 347271391)
  4. 4.0 4.1 "Replicating Sugarscape — University of Leicester". Archived from the original on 2012-06-19. Retrieved 18 January 2011.
  5. "The Ascape Model Developer's Manual". Sourceforge. Retrieved 9 November 2010.
  6. "NetLogo User Community Models: Sugarscape". Retrieved 9 November 2010.
  7. "The Sugarscape". University of Leicester. Archived from the original on 2017-10-02. Retrieved 19 January 2011.
  8. Gilbert, Nigel; Bankes, Steven (2002). "Platforms and Methods for Agent-Based Modelling" (PDF). Proceedings of the National Academy of Sciences. 99 (3): 7197–7198. doi:10.1073/pnas.072079499. PMC 128584. PMID 12011398.
  9. D'Souza, Roshan M.; Lysenko, Mikola; Rahmani, Keyvan (2007). "SugarScape on steroids: simulating over a million agents at interactive rates" (PDF). Proceedings of Agent2007 Conference. Chicago, Il.(See also: presentation slides)
  10. "Sugarscape: Agent-Based Modeling - Wolfram Demonstrations Project". Wolfram. Retrieved 18 January 2011.
  11. Bigbee, Anthony; Cioffi-Revilla, Claudio; Luke, Sean (2007). Terano, T.; Kita, H.; Deguchi, H.; et al. (eds.). "Replication of Sugarscape Using MASON" (PDF). Agent-Based Approaches in Economic and Social Complex Systems IV: Post-Proceedings of the AESCS International Workshop 2005. Tokyo: Springer.

External links