The history of the agent-based model can be traced back to the [[Self-replicating machine|Von Neumann machine]], a theoretical machine capable of reproducing itself. The device [[John von Neumann|von Neumann]] proposed would follow precisely detailed instructions to fashion a copy of itself. The concept was then improved by von Neumann's friend [[Stanislaw Ulam]], also a mathematician; Ulam suggested that the machine be built on paper, as a collection of cells on a grid. The idea intrigued von Neumann, who drew it up—creating the first of devices later termed [[cellular automata]].
−
−
The history of the agent-based model can be traced back to the Von Neumann machine, a theoretical machine capable of reproducing itself. The device von Neumann proposed would follow precisely detailed instructions to fashion a copy of itself. The concept was then improved by von Neumann's friend Stanislaw Ulam, also a mathematician; Ulam suggested that the machine be built on paper, as a collection of cells on a grid. The idea intrigued von Neumann, who drew it up—creating the first of devices later termed cellular automata.
Another improvement was brought by mathematician, [[John Horton Conway|John Conway]]. He constructed the well-known [[Conway's Game of Life|Game of Life]]. Unlike the von Neumann's machine, Conway's Game of Life operated by simple rules in a virtual world in the form of a 2-dimensional [[checkerboard]].
−
−
Another improvement was brought by mathematician, John Conway. He constructed the well-known Game of Life. Unlike the von Neumann's machine, Conway's Game of Life operated by simple rules in a virtual world in the form of a 2-dimensional checkerboard.
数学家[[John Horton Conway|John Conway]]带来了另一项改进。他构建了著名的生命游戏。与冯 · 诺依曼的机器不同,康威的“生命的游戏”([[Conway's Game of Life|Game of Life]])以二维棋盘的形式在虚拟世界中按照简单的规则运行。
数学家[[John Horton Conway|John Conway]]带来了另一项改进。他构建了著名的生命游戏。与冯 · 诺依曼的机器不同,康威的“生命的游戏”([[Conway's Game of Life|Game of Life]])以二维棋盘的形式在虚拟世界中按照简单的规则运行。
−
−
The birth of the agent-based model as a model for social systems was primarily brought about by a computer scientist, [[Craig Reynolds (computer graphics)|Craig Reynolds]]. He tried to model the reality of lively biological agents, known as the [[artificial life]], a term coined by [[Christopher Langton]].
−
−
The birth of the agent-based model as a model for social systems was primarily brought about by a computer scientist, Craig Reynolds. He tried to model the reality of lively biological agents, known as the artificial life, a term coined by Christopher Langton.
[[Joshua M. Epstein]] and [[Robert Axtell]] developed the first large scale agent model, the [[Sugarscape]], to simulate and explore the role of social phenomena such as seasonal migrations, pollution, sexual reproduction, combat, transmission of disease, and even culture.
−
−
Joshua M. Epstein and Robert Axtell developed the first large scale agent model, the Sugarscape, to simulate and explore the role of social phenomena such as seasonal migrations, pollution, sexual reproduction, combat, transmission of disease, and even culture.
Joshua M. Epstein 和 Robert Axtell 开发了第一个大规模的agent模型---- Sugarscape,用来模拟和探索诸如季节性迁徙、污染、有性生殖、战斗、疾病传播甚至文化等社会现象的作用。
Joshua M. Epstein 和 Robert Axtell 开发了第一个大规模的agent模型---- Sugarscape,用来模拟和探索诸如季节性迁徙、污染、有性生殖、战斗、疾病传播甚至文化等社会现象的作用。
−
[[Kathleen M. Carley]] published "Computational Organizational Science and Organizational Engineering" defining the movement of simulation into organizations, established a journal for social simulation applied to organizations and complex socio-technical systems: [[Computational and Mathematical Organization Theory]], and was the founding president of the North American Association of Computational Social and Organizational Systems that morphed into the current CSSSA.
−
−
Kathleen M. Carley published "Computational Organizational Science and Organizational Engineering" defining the movement of simulation into organizations, established a journal for social simulation applied to organizations and complex socio-technical systems: Computational and Mathematical Organization Theory, and was the founding president of the North American Association of Computational Social and Organizational Systems that morphed into the current CSSSA.
Kathleen M. Carley发表了“计算机组织科学和组织工程学”(Computational Organizational Science and Organizational Engineering) ,定义了模拟在组织的过程,创办了一本应用于组织和复杂社会技术系统的社会模拟期刊:《计算机和数学组织理论》(Computational and Mathematical Organization Theory) ,并且是北美计算机社会和组织系统协会(North American Association of Computational Social and Organizational Systems)的创始主席,该协会后来演变成了现在的 CSSSA。
Kathleen M. Carley发表了“计算机组织科学和组织工程学”(Computational Organizational Science and Organizational Engineering) ,定义了模拟在组织的过程,创办了一本应用于组织和复杂社会技术系统的社会模拟期刊:《计算机和数学组织理论》(Computational and Mathematical Organization Theory) ,并且是北美计算机社会和组织系统协会(North American Association of Computational Social and Organizational Systems)的创始主席,该协会后来演变成了现在的 CSSSA。
−
[[Nigel Gilbert]] published with [[Klaus G. Troitzsch]] the first textbook on Social Simulation: Simulation for the Social Scientist (1999) and established its most relevant journal: the [[Journal of Artificial Societies and Social Simulation]].
−
Nigel Gilbert published with Klaus G. Troitzsch the first textbook on Social Simulation: Simulation for the Social Scientist (1999) and established its most relevant journal: the Journal of Artificial Societies and Social Simulation.
+
[[Nigel Gilbert]] 与 [[Klaus G. Troitzsch]] 共同出版了第一本关于社会模拟的教科书:《社会模拟: 社会科学家的模拟》(1999年) ,并创办了其最相关的的期刊: 《人工社会与社会模拟杂志(Journal of Artificial Societies and Social Simulation)》。
−
[[Nigel Gilbert]] 与 [[Klaus G. Troitzsch]] 共同出版了第一本关于社会模拟的教科书:《社会模拟: 社会科学家的模拟》(1999年) ,并创办了其最相关的的期刊: 《人工社会与社会模拟杂志》([[Journal of Artificial Societies and Social Simulation]])。
+
最近,Ron Sun 开发了一种基于人类认知模型的基于 agent 的模拟方法,称为认知社会模拟(cognitive social simulation)
−
More recently, [[Ron Sun]] developed methods for basing agent-based simulation on models of human cognition, known as [[cognitive social simulation]] (see {{Harv|Sun|2006}})【原网页应该是(see (Sun 2006)】.
−
More recently, Ron Sun developed methods for basing agent-based simulation on models of human cognition, known as cognitive social simulation 【原网页应该是(see (Sun 2006)(超链接】.
+
== 主题 ==
−
最近,Ron Sun 开发了一种基于人类认知模型的基于 agent 的模拟方法,称为认知社会模拟(cognitive social simulation)
−
==Topics==
+
下面是一些已经用社交模拟探索过的样本主题:
−
==Topics==
−
= = 主题 = =
+
* '''社会规范''': Robert Axelrod使用模拟来研究道德的基础<ref>Robert Axelrod (1986): [http://www-personal.umich.edu/~axe/Axelrod%20Norms%20APSR%201986%20(2).pdf An Evolutionary Approach to Norms]</ref>; 其他人使用模因模拟了规范的出现<ref>Felix Flentge, Daniel Polani and Thomas Uthmann (2001) [http://jasss.soc.surrey.ac.uk/4/4/3.html Modelling the Emergence of Possession Norms using Memes]</ref>,或者社会规范和情绪可以互相调节<ref>Alexander Staller and Paolo Petta (2001): [http://jasss.soc.surrey.ac.uk/4/1/2.html Introducing Emotions into the Computational Study of Social Norms: A First Evaluation]</ref><ref>See Martin Neumann (2008): [http://jasss.soc.surrey.ac.uk/11/4/6.html Homo Socionicus: a Case Study of Simulation Models of Norms] for an overview of the recent (as of 2008) research.</ref>。
−
Here are some sample topics that have been explored with social simulation:
−
Here are some sample topics that have been explored with social simulation:
+
* '''制度''':通过调查代理人在什么条件下设法协调<ref>José Castro Caldas and Helder Coelho (1999): [http://jasss.soc.surrey.ac.uk/2/2/1.html The Origin of Institutions: socio-economic processes, choice, norms and conventions]</ref>,或者通过模仿[[Robert Putnam]]的公民传统著作<ref>Dan Miodownik, Britt Cartrite and Ravi Bhavnani (2010): [http://jasss.soc.surrey.ac.uk/13/3/1.html Between Replication and Docking: "Adaptive Agents, Political Institutions, and Civic Traditions" Revisited]</ref>。
−
下面是一些已经用社交模拟探索过的样本主题:
+
* '''声誉''':例如通过使用[[Pierre Bourdieu]]的声誉模型(形象,社会尊重和声望),并观察他们在虚拟市场中的行为。 <ref>Christian Hahn, Bettina Fley, Michael Florian, Daniela Spresny and Klaus Fischer (2007) : [http://jasss.soc.surrey.ac.uk/10/1/2.html Social Reputation: a Mechanism for Flexible Self-Regulation of Multiagent Systems]</ref>
−
* '''[[norm (social)|Social norms]]''': [[Robert Axelrod]] has used simulations to investigate the foundation of morality;<ref>Robert Axelrod (1986): [http://www-personal.umich.edu/~axe/Axelrod%20Norms%20APSR%201986%20(2).pdf An Evolutionary Approach to Norms]</ref> others have modeled the emergence of norms using [[meme]]s,<ref>Felix Flentge, Daniel Polani and Thomas Uthmann (2001) [http://jasss.soc.surrey.ac.uk/4/4/3.html Modelling the Emergence of Possession Norms using Memes]</ref> or how social norms and emotions can regulate each other.<ref>Alexander Staller and Paolo Petta (2001): [http://jasss.soc.surrey.ac.uk/4/1/2.html Introducing Emotions into the Computational Study of Social Norms: A First Evaluation]</ref><ref>See Martin Neumann (2008): [http://jasss.soc.surrey.ac.uk/11/4/6.html Homo Socionicus: a Case Study of Simulation Models of Norms] for an overview of the recent (as of 2008) research.</ref>
−
* 社会规范: Robert Axelrod使用模拟来研究道德的基础[3]; 其他人使用模因模拟了规范的出现[4],或者社会规范和情绪可以互相调节[5][6]。
−
*
−
* '''[[Institutions]]''': by investigating under what conditions agents manage to coordinate,<ref>José Castro Caldas and Helder Coelho (1999): [http://jasss.soc.surrey.ac.uk/2/2/1.html The Origin of Institutions: socio-economic processes, choice, norms and conventions]</ref> or by modeling the works of [[Robert Putnam]] on civic traditions<ref>Dan Miodownik, Britt Cartrite and Ravi Bhavnani (2010): [http://jasss.soc.surrey.ac.uk/13/3/1.html Between Replication and Docking: "Adaptive Agents, Political Institutions, and Civic Traditions" Revisited]</ref>
* '''[[Reputation]]''', for example by making agents with a model of reputation from [[Pierre Bourdieu]] (image, social esteem, and prestige) and observing their behavior in a virtual marketplace.<ref>Christian Hahn, Bettina Fley, Michael Florian, Daniela Spresny and Klaus Fischer (2007) : [http://jasss.soc.surrey.ac.uk/10/1/2.html Social Reputation: a Mechanism for Flexible Self-Regulation of Multiagent Systems]</ref>
* '''Knowledge transmission''' and the social process of science: there is a special section on that topic in the [[Journal of Artificial Societies and Social Simulation]]<ref>[http://jasss.soc.surrey.ac.uk/14/4/contents.html JASSS vol. 14: Special section: Simulating the Social Processes of Science]</ref>
−
* 知识传播和科学的社会过程:在人工社会和社会模拟杂志([[Journal of Artificial Societies and Social Simulation]])上有一个关于这个主题的特别部分[10]。
−
*
−
* '''[[Elections]]''': Kim (2011) has modeled a psychological model of judgement from previous research (notably featuring [[motivated reasoning]]), and compared the statistical regularities of the simulation with empirical observations of voter behavior;<ref>Sung-youn Kim (2011): [http://jasss.soc.surrey.ac.uk/14/2/3.html A Model of Political Judgment: An Agent-Based Simulation of Candidate Evaluation]</ref> others have compared delegation methods.<ref>Ramzi Suleiman and Ilan Fischer (2000) [http://jasss.soc.surrey.ac.uk/3/4/1.html When One Decides for Many: The Effect of Delegation Methods on Cooperation in Simulated Inter-group Conflicts]</ref><ref>Marie-Edith Bissey, Mauro Carini and Guido Ortona (2004) [http://jasss.soc.surrey.ac.uk/7/3/3.html ALEX3, a Simulation Program to Compare Electoral Systems]</ref>
* '''知识传播和科学的社会过程''':在人工社会和社会模拟杂志([[Journal of Artificial Societies and Social Simulation]])上有一个关于这个主题的特别部分<ref>[http://jasss.soc.surrey.ac.uk/14/4/contents.html JASSS vol. 14: Special section: Simulating the Social Processes of Science]</ref>。
−
(下面这段和原网页不太一样,我不知道是从哪找找的,就没动。我前面那段按照原网页翻译的,这边我没改)
+
* '''选举''':Kim(2011)模拟了之前研究中的判断心理模型(明显具有动机的推理),并对比了模拟的统计规律和选民行为的经验观察<ref>Sung-youn Kim (2011): [http://jasss.soc.surrey.ac.uk/14/2/3.html A Model of Political Judgment: An Agent-Based Simulation of Candidate Evaluation]</ref>,其他人比较了委托方法。<ref>Ramzi Suleiman and Ilan Fischer (2000) [http://jasss.soc.surrey.ac.uk/3/4/1.html When One Decides for Many: The Effect of Delegation Methods on Cooperation in Simulated Inter-group Conflicts]</ref><ref>Marie-Edith Bissey, Mauro Carini and Guido Ortona (2004) [http://jasss.soc.surrey.ac.uk/7/3/3.html ALEX3, a Simulation Program to Compare Electoral Systems]</ref>
−
* 【Social norms: Robert Axelrod has used simulations to investigate the foundation of morality;Robert Axelrod (1986): An Evolutionary Approach to Norms others have modeled the emergence of norms using memes,Felix Flentge, Daniel Polani and Thomas Uthmann (2001) Modelling the Emergence of Possession Norms using Memes or how social norms and emotions can regulate each other.Alexander Staller and Paolo Petta (2001): Introducing Emotions into the Computational Study of Social Norms: A First EvaluationSee Martin Neumann (2008): Homo Socionicus: a Case Study of Simulation Models of Norms for an overview of the recent (as of 2008) research.
−
* Institutions: by investigating under what conditions agents manage to coordinate,José Castro Caldas and Helder Coelho (1999): The Origin of Institutions: socio-economic processes, choice, norms and conventions or by modeling the works of Robert Putnam on civic traditionsDan Miodownik, Britt Cartrite and Ravi Bhavnani (2010): Between Replication and Docking: "Adaptive Agents, Political Institutions, and Civic Traditions" Revisited
−
* Reputation, for example by making agents with a model of reputation from Pierre Bourdieu (image, social esteem, and prestige) and observing their behavior in a virtual marketplace.Christian Hahn, Bettina Fley, Michael Florian, Daniela Spresny and Klaus Fischer (2007) : Social Reputation: a Mechanism for Flexible Self-Regulation of Multiagent Systems
−
* Knowledge transmission and the social process of science: there is a special section on that topic in the Journal of Artificial Societies and Social SimulationJASSS vol. 14: Special section: Simulating the Social Processes of Science
−
* Elections: Kim (2011) has modeled a psychological model of judgement from previous research (notably featuring motivated reasoning), and compared the statistical regularities of the simulation with empirical observations of voter behavior;Sung-youn Kim (2011): A Model of Political Judgment: An Agent-Based Simulation of Candidate Evaluation others have compared delegation methods.Ramzi Suleiman and Ilan Fischer (2000) When One Decides for Many: The Effect of Delegation Methods on Cooperation in Simulated Inter-group ConflictsMarie-Edith Bissey, Mauro Carini and Guido Ortona (2004) ALEX3, a Simulation Program to Compare Electoral Systems.
* 选举的社会过程: Kim (2011)根据以前的研究建立了一个判断的心理模型(特别是动机性推理) ,并将模拟的统计规律与选民行为的实证观察进行了比较; Sung-youn Kim (2011) : 政治判断模型: 基于 agent 的候选人评估模拟其他人比较了授权方法。Ramzi Suleiman and Ilan Fischer (2000) When One decide for Many: The Effect of Delegation Methods on Cooperation in Simulated Inter-group conflict. marie-edith Bissey,Mauro Carini and Guido Ortona (2004) ALEX3,a Simulation Program to Compare Electoral Systems
Social simulation can refer to a general class of strategies for understanding social dynamics using computers to simulate social systems. Social simulation allows for a more systematic way of viewing the possibilities of outcomes.
−
Social simulation can refer to a general class of strategies for understanding social dynamics using computers to simulate social systems. Social simulation allows for a more systematic way of viewing the possibilities of outcomes.
A social simulation may fall within the rubric of [[computational sociology]] which is a recently developed branch of [[sociology]] that uses [[computation]] to analyze social phenomena. The basic premise of computational sociology is to take advantage of [[computer simulation]]s {{Harv|Polhill|Edmonds|2007}} in the construction of social theories. It involves the understanding of [[social agent]]s, the interaction among these agents, and the effect of these interactions on the social aggregate. Although the subject matter and methodologies in [[social science]] differ from those in [[natural science]] or [[computer science]], several of the approaches used in contemporary social [[simulation]] originated from fields such as [[physics]] and [[artificial intelligence]].
+
#基于 agent 的建模。
−
A social simulation may fall within the rubric of computational sociology which is a recently developed branch of sociology that uses computation to analyze social phenomena. The basic premise of computational sociology is to take advantage of computer simulations in the construction of social theories. It involves the understanding of social agents, the interaction among these agents, and the effect of these interactions on the social aggregate. Although the subject matter and methodologies in social science differ from those in natural science or computer science, several of the approaches used in contemporary social simulation originated from fields such as physics and artificial intelligence.
System Level Simulation (SLS) is the oldest level of social simulation. System level simulation looks at the situation as a whole. This theoretical outlook on social situations uses a wide range of information to determine what should happen to society and its members if certain variables are present. Therefore, with specific variables presented, society and its members should have a certain response to the new situation. Navigating through this theoretical simulation will allow researchers to develop educated ideas of what will happen under some specific variables.
−
−
System Level Simulation (SLS) is the oldest level of social simulation. System level simulation looks at the situation as a whole. This theoretical outlook on social situations uses a wide range of information to determine what should happen to society and its members if certain variables are present. Therefore, with specific variables presented, society and its members should have a certain response to the new situation. Navigating through this theoretical simulation will allow researchers to develop educated ideas of what will happen under some specific variables.
For example, if [[NASA]] were to conduct a system level simulation it would benefit the organization by providing a cost-effective research method to navigate through the simulation. This allows the researcher to steer through the virtual possibilities of the given simulation and develop [[safety]] procedures, and to produce proven facts about how a certain situation will play out. 【( (National Research 2006)】
−
−
For example, if NASA were to conduct a system level simulation it would benefit the organization by providing a cost-effective research method to navigate through the simulation. This allows the researcher to steer through the virtual possibilities of the given simulation and develop safety procedures, and to produce proven facts about how a certain situation will play out.
System level modeling (SLM) aims to specifically predict (unlike system level simulation's generalization in prediction) and convey any number of actions, behaviors, or other theoretical possibilities of nearly any person, object, construct et cetera within a system using a large set of mathematical equations and computer programming in the form of models.
−
−
System level modeling (SLM) aims to specifically predict (unlike system level simulation's generalization in prediction) and convey any number of actions, behaviors, or other theoretical possibilities of nearly any person, object, construct et cetera within a system using a large set of mathematical equations and computer programming in the form of models.
A model is a representation of a specific thing ranging from objects and people to structures and products created through mathematical equations and are designed, using computers, in such a way that they are able to stand-in as the aforementioned things in a study. Models can be either simplistic or complex, depending on the need for either; however, models are intended to be simpler than what they are representing while remaining realistically similar in order to be used accurately. They are built using a collection of data that is translated into computing languages that allow them to represent the system in question. These models, much like simulations, are used to help us better understand specific roles and actions of different things so as to predict behavior and the like.
−
−
A model is a representation of a specific thing ranging from objects and people to structures and products created through mathematical equations and are designed, using computers, in such a way that they are able to stand-in as the aforementioned things in a study. Models can be either simplistic or complex, depending on the need for either; however, models are intended to be simpler than what they are representing while remaining realistically similar in order to be used accurately. They are built using a collection of data that is translated into computing languages that allow them to represent the system in question. These models, much like simulations, are used to help us better understand specific roles and actions of different things so as to predict behavior and the like.
[[Agent-based social simulation]] (ABSS) consists of modeling different societies after artificial agents, (varying on scale) and placing them in a computer simulated society to observe the behaviors of the agents. From this data it is possible to learn about the reactions of the artificial agents and translate them into the results of non-artificial agents and simulations. Three main fields in ABSS are agent-based computing, social science, and computer simulation.
−
−
Agent-based social simulation (ABSS) consists of modeling different societies after artificial agents, (varying on scale) and placing them in a computer simulated society to observe the behaviors of the agents. From this data it is possible to learn about the reactions of the artificial agents and translate them into the results of non-artificial agents and simulations. Three main fields in ABSS are agent-based computing, social science, and computer simulation.
基于agent的社会模拟([[Agent-based social simulation]],ABSS)是将不同社会群体按照人工智能(artificial agent)模型(规模不同)进行建模,并将其置于计算机模拟的社会中,以观察agents的行为。从这些数据可以了解人工代理的反应,并将其转化为非人工代理和模拟的结果。ABSS 的3个主要领域是基于agent的计算、社会科学和计算机模拟。
基于agent的社会模拟([[Agent-based social simulation]],ABSS)是将不同社会群体按照人工智能(artificial agent)模型(规模不同)进行建模,并将其置于计算机模拟的社会中,以观察agents的行为。从这些数据可以了解人工代理的反应,并将其转化为非人工代理和模拟的结果。ABSS 的3个主要领域是基于agent的计算、社会科学和计算机模拟。
−
−
Agent-based computing is the design of the model and agents, while the computer simulation is the part of the simulation of the agents in the model and the outcomes. The social science is a mixture of sciences and social part of the model. It is where the social phenomena is developed and theorized. The main purpose of ABSS is to provide models and tools for agent-based simulation of social phenomena. With ABSS we can explore different outcomes for phenomena where we might not be able to view the outcome in real life. It can provide us valuable information on society and the outcomes of social events or phenomena.
−
−
Agent-based computing is the design of the model and agents, while the computer simulation is the part of the simulation of the agents in the model and the outcomes. The social science is a mixture of sciences and social part of the model. It is where the social phenomena is developed and theorized. The main purpose of ABSS is to provide models and tools for agent-based simulation of social phenomena. With ABSS we can explore different outcomes for phenomena where we might not be able to view the outcome in real life. It can provide us valuable information on society and the outcomes of social events or phenomena.
[[Agent-based modeling]] (ABM) is a system in which a collection of agents independently interact on networks. Each individual agent is responsible for different behaviors that result in collective behaviors. These behaviors as a whole help to define the workings of the network. ABM focuses on human social interactions and how people work together and communicate with one another without having one, single "group mind". This essentially means that it tends to focus on the consequences of interactions between people (the agents) in a population. Researchers are better able to understand this type of modeling by modeling these dynamics on a smaller, more localized level. Essentially, ABM helps to better understand interactions between people (agents) who, in turn, influence one another (in response to these influences). Simple individual rules or actions can result in coherent [[group behavior]]. Changes in these individual acts can affect the collective group in any given population.
−
−
Agent-based modeling (ABM) is a system in which a collection of agents independently interact on networks. Each individual agent is responsible for different behaviors that result in collective behaviors. These behaviors as a whole help to define the workings of the network. ABM focuses on human social interactions and how people work together and communicate with one another without having one, single "group mind". This essentially means that it tends to focus on the consequences of interactions between people (the agents) in a population. Researchers are better able to understand this type of modeling by modeling these dynamics on a smaller, more localized level. Essentially, ABM helps to better understand interactions between people (agents) who, in turn, influence one another (in response to these influences). Simple individual rules or actions can result in coherent group behavior. Changes in these individual acts can affect the collective group in any given population.
There are several current research projects that relate directly to modeling and agent-based simulation the following are listed below with a brief overview.
−
−
There are several current research projects that relate directly to modeling and agent-based simulation the following are listed below with a brief overview.
有几个当前的研究项目与建模和基于agent的模拟直接相关的,下面列出了一个简短的概述。
有几个当前的研究项目与建模和基于agent的模拟直接相关的,下面列出了一个简短的概述。
−
*"Generative e-Social Science for Socio-Spatial Simulation" or (GENESIS) is a research node of the UK National Centre for e-Social Science funded by the UK research council [http://www.esrc.ac.uk ESRC]. For further details please see: [https://web.archive.org/web/20091209031009/http://www.genesis.ucl.ac.uk/ GENESIS Web Page] and [https://web.archive.org/web/20091114023426/http://www.casa.ucl.ac.uk/genesisblog/ Blog].
*"National e-Infrastructure for Social Simulation" or (NeISS) is a UK-based project funded by [http://www.jisc.ac.uk JISC]. For further details please see: [http://www.neiss.org.uk The NeISS Web Pages].
*"Network Models Governance and R&D collaboration networks" or (N.E.M.O) is a research centre whose main focus is to identify ways to create and to assess desirable network structures for typical functions; (e.g. knowledge, creation, transfer, and distribution.) This research will ultimately aid [[policy-makers]] at all political levels in improving the effectiveness and efficiency of network-based policy instruments at promoting the knowledge economy in Europe.
*"Agent-based Simulations of Market and Consumer Behavior" is another research group that is funded by the Unilever Corporate Research. The current research that is being conducted is investigating the usefulness of agent-based simulations for modeling [[consumer behavior]] and to show the potential value and insights it can add to long-established marketing methods.
*"New and Emergent World Models Through Individual, Evolutionary and Social Learning" or (New Ties) is a three-year project that will ultimately create a virtual society developed by agent-based simulation. The project will develop a simulated society capable of exploring the environment and developing its own image of this environment and the society through interaction. The goal of the research project is for the simulated society to exhibit [[individual learning]], [[evolutionary learning]] and [[social learning (social pedagogy)|social learning]].
*Bruch and Mare's project on neighborhood [[Residential segregation|segregation]]: The purpose of the study is to figure out the reasoning for neighborhood segregation based on [[Race (classification of human beings)|race]], and to figure out the [[tipping point (sociology)|tipping point]] or when people become uncomfortable with the integration levels into their neighborhood, and decide to flee from the neighborhood. They set up a model using flash cards, and put the agent's house in the middle and put houses of different races surrounding the agent's house. They asked people how comfortable they would feel with different situations; if they were okay with one situation, they asked another until the neighborhood was fully integrated. Bruch and Mare's results showed that the tipping point was at 50%. When a neighborhood became 50% minority and 50% white, people of both races began to become uncomfortable and [[white flight]] began to rise. The use of agent-based modeling showed how useful it can be in the world of sociology, people did not have to answer why they would become uncomfortable, just which situation they were uncomfortable with.
−
*
* Bruch和 Mare 的关于社区隔离的项目: 这项研究的目的是找出基于种族的社区隔离的原因,并找出临界点或者当人们对融入社区的程度感到不舒服时,并决定逃离社区时。他们用闪存卡建立了一个模型,然后把agent的房子放在中间,把不同种族的房子围绕在agent的房子周围。他们询问人们在不同的情况下感觉如何; 如果他们对一种情况感到没问题,他们会询问另一种情况,直到邻里完全融合。Bruch 和 Mare 的研究结果显示,临界点是50% 。当一个社区变成了50% 的少数民族和50% 的白人时,这两个种族的人开始变得不舒服,白人逃亡开始增多。基于agent的模型的使用表明它在社会学领域是多么的有用,人们不需要回答为什么他们会变得不舒服,只需要回答他们对哪种情况感到不舒服。
* Bruch和 Mare 的关于社区隔离的项目: 这项研究的目的是找出基于种族的社区隔离的原因,并找出临界点或者当人们对融入社区的程度感到不舒服时,并决定逃离社区时。他们用闪存卡建立了一个模型,然后把agent的房子放在中间,把不同种族的房子围绕在agent的房子周围。他们询问人们在不同的情况下感觉如何; 如果他们对一种情况感到没问题,他们会询问另一种情况,直到邻里完全融合。Bruch 和 Mare 的研究结果显示,临界点是50% 。当一个社区变成了50% 的少数民族和50% 的白人时,这两个种族的人开始变得不舒服,白人逃亡开始增多。基于agent的模型的使用表明它在社会学领域是多么的有用,人们不需要回答为什么他们会变得不舒服,只需要回答他们对哪种情况感到不舒服。
−
*
+
−
*The MAELIA Program (Multi-Agent Emergent Norms Assessment) is a project dealing with the relationships between the users and managers of a natural resource, in that case water, and the related norms and laws that are to be built within them (conventions) or are imposed to them by other actors (institutions). The purpose of the project is to build a generic multiscale platform which is planned to deal with [[water conflict]]-related issues.
*The [http://www.gsi.dit.upm.es/mosi/ Mosi-Agil project] is a four-year program funded by the Autonomous Region of Madrid through the program MOSI-AGIL-CM (grant S2013/ICE-3019, co-funded by EU Structural Funds FSE and FEDER). It aims at creating a body of knowledge and practical tools which are necessary to handle more effectively the behavior of occupants of large facilities. Therefore, the project studies the development of ambient intelligence and intelligent environments supported by the use of Agent-Based Social Simulation.
Agent-based modeling is most useful in providing a bridge between micro and macro levels, which is a large part of what sociology studies. Agent-based models are most appropriate for studying processes that lack central coordination, including the emergence of institutions that, once established, impose order from the top down. The models focus on how simple and predictable local interactions generate familiar but highly detailed global patterns, such as emergence of [[norm (sociology)|norms]] and [[participation (decision making)|participation]] of collective action. Michael W. Macy and Robert Willer researched a recent survey of applications and found that there were two main problems with agent-based modeling the [[self-organization]] of social structure and the [[emergence]] of [[social order]] 【(Macy & Willer 2002)】. Below is a brief description of each problem Macy and Willer believe there to be;
基于 agent 的建模在微观层面和宏观层面之间架起了一座桥梁,这是社会学研究的重要组成部分。基于agent的模型最适合于研究中缺乏中央协调的过程,包括出现的机构,一旦建立,从上到下施加秩序。这些模式侧重于简单且可预测的本地互动如何产生熟悉但非常详细的全球模式,如规范的出现和集体行动的参与。Michael W. Macy 和 Robert Willer 研究了最近的一项应用调查,发现基于 agent 的社会结构的自组织建模和社会秩序的出现存在两个主要问题。下面是Macy and Willer 认为存在的每个问题的简要描述:
基于 agent 的建模在微观层面和宏观层面之间架起了一座桥梁,这是社会学研究的重要组成部分。基于agent的模型最适合于研究中缺乏中央协调的过程,包括出现的机构,一旦建立,从上到下施加秩序。这些模式侧重于简单且可预测的本地互动如何产生熟悉但非常详细的全球模式,如规范的出现和集体行动的参与。Michael W. Macy 和 Robert Willer 研究了最近的一项应用调查,发现基于 agent 的社会结构的自组织建模和社会秩序的出现存在两个主要问题。下面是Macy and Willer 认为存在的每个问题的简要描述:
−
#"''Emergent structure''. In these models, agents change location or behavior in response to [[social influences]] or selection pressures. Agents may start out undifferentiated and then change location or behavior so as to avoid becoming different or isolated (or in some cases, overcrowded). Rather than producing homogeneity, however, these conformist decisions aggregate to produce global patterns of cultural differentiation, stratification, and homophilic clustering in local networks. Other studies reverse the process, starting with a heterogeneous population and ending in convergence: the coordination, diffusion, and sudden collapse of norms, conventions, innovations, and technological standards."
−
#"''Emergent social order''. These studies show how [[egotism|egoistic]] adaptation can lead to successful collective action without either altruism or global (top down) imposition of control. A key finding across numerous studies is that the viability of trust, cooperation, and collective action depends decisively on the embeddedness of interaction."
These examples simply show the complexity of our environment and that agent-based models are designed to explore the minimal conditions, the simplest set of assumptions about human behavior, required for a given social phenomenon to emerge at a higher level of organization.
−
−
These examples simply show the complexity of our environment and that agent-based models are designed to explore the minimal conditions, the simplest set of assumptions about human behavior, required for a given social phenomenon to emerge at a higher level of organization.
Since its creation, computerized social simulation has been the target of some criticism in regard to its practicality and accuracy. Social simulation's simplification of the complex to form models from which we can better understand the latter is sometimes seen as a draw back, as using fairly simple models to simulate real life with computers is not always the best way to predict behavior.
−
−
Since its creation, computerized social simulation has been the target of some criticism in regard to its practicality and accuracy. Social simulation's simplification of the complex to form models from which we can better understand the latter is sometimes seen as a draw back, as using fairly simple models to simulate real life with computers is not always the best way to predict behavior.
Most of the criticism seems to be aimed at agent-based models and simulation and how they work:
−
−
Most of the criticism seems to be aimed at agent-based models and simulation and how they work:
大多数批评似乎都针对基于agent的模型和模拟,以及它们的工作方式:
大多数批评似乎都针对基于agent的模型和模拟,以及它们的工作方式:
−
#Simulations, being man-made from mathematical interfaces, predict [[human behavior]] in a far too simple manner in regard to the complexities of humanity and our actions.
−
#Simulations cannot enlighten researchers as to how people interact or behave in ways not programmed into their models. For this reason, the scope of simulations are limited in that the researchers must already know what they are going to find (to a degree, for they cannot find anything they themselves did not place in the model) at least vaguely, possibly skewing the results.
−
#Due to the complexities of what is being measured, simulations must be analyzed in unbiased ways; however, with the model running on a pre-made set of instructions coded into it by a modeler, biases exist almost universally.
−
#It is highly difficult and often impractical to attempt to link the findings from the abstract world the simulation creates and our complex society and all of its variation.
Researchers working in social simulation might respond that the competing theories from the [[social sciences]] are far simpler than those achieved through simulation and therefore suffer the aforementioned drawbacks much more strongly. Theories in some social science tend to be linear models that are not dynamic, and are generally inferred from small laboratory [[experiment]]s (laboratory tests are most common in psychology but rare in sociology, political science, economics and geography). The behavior of populations of agents under these models is rarely tested or verified against empirical observation.
−
−
Researchers working in social simulation might respond that the competing theories from the social sciences are far simpler than those achieved through simulation and therefore suffer the aforementioned drawbacks much more strongly. Theories in some social science tend to be linear models that are not dynamic, and are generally inferred from small laboratory experiments (laboratory tests are most common in psychology but rare in sociology, political science, economics and geography). The behavior of populations of agents under these models is rarely tested or verified against empirical observation.
Joshua M. Epstein 和 Robert Axtell 开发了第一个大规模的agent模型---- Sugarscape,用来模拟和探索诸如季节性迁徙、污染、有性生殖、战斗、疾病传播甚至文化等社会现象的作用。
Kathleen M. Carley发表了“计算机组织科学和组织工程学”(Computational Organizational Science and Organizational Engineering) ,定义了模拟在组织的过程,创办了一本应用于组织和复杂社会技术系统的社会模拟期刊:《计算机和数学组织理论》(Computational and Mathematical Organization Theory) ,并且是北美计算机社会和组织系统协会(North American Association of Computational Social and Organizational Systems)的创始主席,该协会后来演变成了现在的 CSSSA。
Nigel Gilbert 与 Klaus G. Troitzsch 共同出版了第一本关于社会模拟的教科书:《社会模拟: 社会科学家的模拟》(1999年) ,并创办了其最相关的的期刊: 《人工社会与社会模拟杂志(Journal of Artificial Societies and Social Simulation)》。
最近,Ron Sun 开发了一种基于人类认知模型的基于 agent 的模拟方法,称为认知社会模拟(cognitive social simulation)
主题
下面是一些已经用社交模拟探索过的样本主题:
社会规范: Robert Axelrod使用模拟来研究道德的基础[3]; 其他人使用模因模拟了规范的出现[4],或者社会规范和情绪可以互相调节[5][6]。
基于agent的社会模拟(Agent-based social simulation,ABSS)是将不同社会群体按照人工智能(artificial agent)模型(规模不同)进行建模,并将其置于计算机模拟的社会中,以观察agents的行为。从这些数据可以了解人工代理的反应,并将其转化为非人工代理和模拟的结果。ABSS 的3个主要领域是基于agent的计算、社会科学和计算机模拟。
Agent-based modeling is an experimental tool for theoretical research. It enables one to deal with more complex individual behaviors, such as adaptation. Overall, through this type of modeling, the creator, or researcher, aims to model behavior of agents and the communication between them in order to better understand how these individual interactions impact an entire population. In essence, ABM is a way of modeling and understanding different global patterns.
Agent-based modeling is an experimental tool for theoretical research. It enables one to deal with more complex individual behaviors, such as adaptation. Overall, through this type of modeling, the creator, or researcher, aims to model behavior of agents and the communication between them in order to better understand how these individual interactions impact an entire population. In essence, ABM is a way of modeling and understanding different global patterns.
基于 agent 的建模在微观层面和宏观层面之间架起了一座桥梁,这是社会学研究的重要组成部分。基于agent的模型最适合于研究中缺乏中央协调的过程,包括出现的机构,一旦建立,从上到下施加秩序。这些模式侧重于简单且可预测的本地互动如何产生熟悉但非常详细的全球模式,如规范的出现和集体行动的参与。Michael W. Macy 和 Robert Willer 研究了最近的一项应用调查,发现基于 agent 的社会结构的自组织建模和社会秩序的出现存在两个主要问题。下面是Macy and Willer 认为存在的每个问题的简要描述:
Hadzibeganovic, Tarik; Stauffer, Dietrich; Schulze, Christian (2008), "Boundary effects in a three-state modified voter model for languages", Physica A: Statistical Mechanics and Its Applications, 387 (13): 3242–3252, arXiv:0711.2757, Bibcode:2008PhyA..387.3242H, doi:10.1016/j.physa.2008.02.003
Sylvan, Donald A. (1998), "Modeling the rise and fall of states", Mershon International Studies Review, 42 (Supplement_2): 377–379, doi:10.2307/254437, JSTOR254437
↑Hughes, H. P. N.; Clegg, C. W.; Robinson, M. A.; Crowder, R. M. (2012). "Agent-based modelling and simulation: The potential contribution to organizational psychology". Journal of Occupational and Organizational Psychology. 85 (3): 487–502. doi:10.1111/j.2044-8325.2012.02053.x.
↑ 2.02.1Crowder, R. M.; Robinson, M. A.; Hughes, H. P. N.; Sim, Y. W. (2012). "The development of an agent-based modeling framework for simulating engineering team work". IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans. 42 (6): 1425–1439. doi:10.1109/TSMCA.2012.2199304.