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A multi-agent system (MAS or "self-organized system") is a computerized system composed of multiple interacting intelligent agents. Multi-agent systems can solve problems that are difficult or impossible for an individual agent or a monolithic system to solve. Intelligence may include methodic, functional, procedural approaches, algorithmic search or reinforcement learning.
A multi-agent system (MAS or "self-organized system") is a computerized system composed of multiple interacting intelligent agents. Multi-agent systems can solve problems that are difficult or impossible for an individual agent or a monolithic system to solve. Intelligence may include methodic, functional, procedural approaches, algorithmic search or reinforcement learning.
'''多主体系统'''（英文：'''Self-organized System''' 或 '''Multi-agent System'''，简称'''MAS'''）是一种由多个相互作用的主体组成的计算系统。多主体系统可以解决一些单个主体或单一性系统难以解决的问题。其智能可能体现在条理性、功能性、程序性的行为方式，以及搜索算法和强化学习上。
'''多主体系统''' '''Self-organized System/'Multi-agent System'''，简称'''MAS'''，是一种由多个相互作用的主体组成的计算系统。多主体系统可以解决一些单个主体或单一性系统难以解决的问题。其智能可能体现在条理性、功能性、程序性的行为方式，以及搜索算法和强化学习上。
Despite considerable overlap, a multi-agent system is not always the same as an [[agent-based model]] (ABM). The goal of an ABM is to search for explanatory insight into the collective behavior of agents (which don't necessarily need to be "intelligent") obeying simple rules, typically in natural systems, rather than in solving specific practical or engineering problems. The terminology of ABM tends to be used more often in the science, and MAS in engineering and technology.<ref name="Niazi-Hussain">{{cite journal |first1=Muaz |last1=Niazi |first2=Amir |last2=Hussain |year=2011 |title=Agent-based Computing from Multi-agent Systems to Agent-Based Models: A Visual Survey |journal=Scientometrics |volume=89 |issue=2 |pages=479–499 |doi=10.1007/s11192-011-0468-9 |url=https://www.researchgate.net/publication/220365334 |format=PDF|arxiv=1708.05872 }}</ref> Applications where multi-agent systems research may deliver an appropriate approach include online trading,<ref>{{cite journal |first1=Alex |last1=Rogers |first2=E. |last2=David |first3=J. |last3=Schiff |first4=N.R. |last4=Jennings |url=http://eprints.ecs.soton.ac.uk/12716/ |title=The Effects of Proxy Bidding and Minimum Bid Increments within eBay Auctions |journal=ACM Transactions on the Web |volume=1 |issue=2 |pages=9–es |year=2007|doi=10.1145/1255438.1255441 |citeseerx=10.1.1.65.4539 }}</ref> disaster response<ref>{{cite journal |first1=Nathan |last1=Schurr |first2=Janusz |last2=Marecki |first3=Milind |last3=Tambe |first4=Paul |last4=Scerri | first5=Nikhil |last5=Kasinadhuni |first6=J.P. |last6=Lewis |url=http://teamcore.usc.edu/papers/2005/SS105SchurrN.pdf |title=The Future of Disaster Response: Humans Working with Multiagent Teams using DEFACTO |year=2005}}</ref><ref>{{cite journal |last1=Genc|first1=Zulkuf |url=http://www.gdmc.nl/gi4dmdocs/Gi4DM_2012_Genc.pdf |title=Agent-based information infrastructure for disaster management |journal=Intelligent Systems for Crisis Management |pages=349–355 |date=2013|display-authors=etal|doi=10.1007/978-3-642-33218-0_26 |isbn=978-3-642-33217-3 |series=Lecture Notes in Geoinformation and Cartography }}</ref> and social structure modelling.<ref>{{cite journal |first1=Ron |last1=Sun|authorlink1=Ron Sun |first2=Isaac |last2=Naveh |url=http://jasss.soc.surrey.ac.uk/7/3/5.html |title=Simulating Organizational Decision-Making Using a Cognitively Realistic Agent Model |journal=Journal of Artificial Societies and Social Simulation}}</ref>
Despite considerable overlap, a multi-agent system is not always the same as an [[agent-based model]] (ABM). The goal of an ABM is to search for explanatory insight into the collective behavior of agents (which don't necessarily need to be "intelligent") obeying simple rules, typically in natural systems, rather than in solving specific practical or engineering problems. The terminology of ABM tends to be used more often in the science, and MAS in engineering and technology.<ref name="Niazi-Hussain">{{cite journal |first1=Muaz |last1=Niazi |first2=Amir |last2=Hussain |year=2011 |title=Agent-based Computing from Multi-agent Systems to Agent-Based Models: A Visual Survey |journal=Scientometrics |volume=89 |issue=2 |pages=479–499 |doi=10.1007/s11192-011-0468-9 |url=https://www.researchgate.net/publication/220365334 |format=PDF|arxiv=1708.05872 }}</ref> Applications where multi-agent systems research may deliver an appropriate approach include online trading,<ref>{{cite journal |first1=Alex |last1=Rogers |first2=E. |last2=David |first3=J. |last3=Schiff |first4=N.R. |last4=Jennings |url=http://eprints.ecs.soton.ac.uk/12716/ |title=The Effects of Proxy Bidding and Minimum Bid Increments within eBay Auctions |journal=ACM Transactions on the Web |volume=1 |issue=2 |pages=9–es |year=2007|doi=10.1145/1255438.1255441 |citeseerx=10.1.1.65.4539 }}</ref> disaster response<ref>{{cite journal |first1=Nathan |last1=Schurr |first2=Janusz |last2=Marecki |first3=Milind |last3=Tambe |first4=Paul |last4=Scerri | first5=Nikhil |last5=Kasinadhuni |first6=J.P. |last6=Lewis |url=http://teamcore.usc.edu/papers/2005/SS105SchurrN.pdf |title=The Future of Disaster Response: Humans Working with Multiagent Teams using DEFACTO |year=2005}}</ref><ref>{{cite journal |last1=Genc|first1=Zulkuf |url=http://www.gdmc.nl/gi4dmdocs/Gi4DM_2012_Genc.pdf |title=Agent-based information infrastructure for disaster management |journal=Intelligent Systems for Crisis Management |pages=349–355 |date=2013|display-authors=etal|doi=10.1007/978-3-642-33218-0_26 |isbn=978-3-642-33217-3 |series=Lecture Notes in Geoinformation and Cartography }}</ref> and social structure modelling.<ref>{{cite journal |first1=Ron |last1=Sun|authorlink1=Ron Sun |first2=Isaac |last2=Naveh |url=http://jasss.soc.surrey.ac.uk/7/3/5.html |title=Simulating Organizational Decision-Making Using a Cognitively Realistic Agent Model |journal=Journal of Artificial Societies and Social Simulation}}</ref>
Despite considerable overlap, a multi-agent system is not always the same as an agent-based model (ABM). The goal of an ABM is to search for explanatory insight into the collective behavior of agents (which don't necessarily need to be "intelligent") obeying simple rules, typically in natural systems, rather than in solving specific practical or engineering problems. The terminology of ABM tends to be used more often in the science, and MAS in engineering and technology. Applications where multi-agent systems research may deliver an appropriate approach include online trading, disaster response and social structure modelling.
Despite considerable overlap, a multi-agent system is not always the same as an agent-based model (ABM). The goal of an ABM is to search for explanatory insight into the collective behavior of agents (which don't necessarily need to be "intelligent") obeying simple rules, typically in natural systems, rather than in solving specific practical or engineering problems. The terminology of ABM tends to be used more often in the science, and MAS in engineering and technology. Applications where multi-agent systems research may deliver an appropriate approach include online trading, disaster response and social structure modelling.
尽管多主体系统和'''基于主体的模型'''（英文：'''Agent-based Model'''，简称'''ABM'''）有着很多的重叠，但是他们并不总是相同的。基于主体的模型目标在于解释那些遵循简单规则、可能并不是很“智能”的主体表现出的集群行为，一般被用于天然系统的研究中，而不是在实践和工程解决具体的问题。因此“基于主体的模型”这个词更多地用在科学研究中，而“多主体系统”则更多地用于工程和技术。有关多主体系统的研究可能会对在线交易、灾害应急、社会结构建模等领域有着良好的应用价值。
尽管多主体系统和'''基于主体的模型''' '''Agent-based Model''' 有着很多的重叠，但是他们并不总是相同的。基于主体的模型目标在于解释那些遵循简单规则、可能并不是很“智能”的主体表现出的'''集群行为'''，一般被用于天然系统的研究中，而不是在实践和工程解决具体的问题。因此“基于主体的模型”这个词更多地用在科学研究中，而“多主体系统”则更多地用于工程和技术。有关多主体系统的研究可能会对在线交易、灾害应急、社会结构建模等领域有着良好的应用价值。
Multi-agent systems consist of agents and their environment. Typically multi-agent systems research refers to software agents. However, the agents in a multi-agent system could equally well be robots, humans or human teams. A multi-agent system may contain combined human-agent teams.
Multi-agent systems consist of agents and their environment. Typically multi-agent systems research refers to software agents. However, the agents in a multi-agent system could equally well be robots, humans or human teams. A multi-agent system may contain combined human-agent teams.
多主体系统由'''主体'''（'''Agent'''）及其所处的环境组成。一般来说，多主体系统研究的是[[软件主体]]。然而，多主体系统中的主体也可以是机器人、人类或人类团体。多主体系统还可以包含人类和其它主体的组合。
多主体系统由'''主体''' '''Agent'''及其所处的环境组成。一般来说，多主体系统研究的是[[软件主体]]。然而，多主体系统中的主体也可以是机器人、人类或人类团体。多主体系统还可以包含人类和其它主体的组合。
Agent environments can also be organized according to properties such as accessibility (whether it is possible to gather complete information about the environment), determinism (whether an action causes a definite effect), dynamics (how many entities influence the environment in the moment), discreteness (whether the number of possible actions in the environment is finite), episodicity (whether agent actions in certain time periods influence other periods), and dimensionality (whether spatial characteristics are important factors of the environment and the agent considers space in its decision making). Agent actions are typically mediated via an appropriate middleware. This middleware offers a first-class design abstraction for multi-agent systems, providing means to govern resource access and agent coordination.
Agent environments can also be organized according to properties such as accessibility (whether it is possible to gather complete information about the environment), determinism (whether an action causes a definite effect), dynamics (how many entities influence the environment in the moment), discreteness (whether the number of possible actions in the environment is finite), episodicity (whether agent actions in certain time periods influence other periods), and dimensionality (whether spatial characteristics are important factors of the environment and the agent considers space in its decision making). Agent actions are typically mediated via an appropriate middleware. This middleware offers a first-class design abstraction for multi-agent systems, providing means to govern resource access and agent coordination.
我们也可以从如下角度考察主体所处的环境，如：可知性（是否可以搜集到关于环境的完整信息）、确定性（行为造成的影响是否是确定的）、动态性（同一时刻有多少主体影响环境）、离散性（主体可以采取的行动是否是有限的）、时序性（主体在某一特定时段内的行为是否影响其它时段）、维度性（环境是否具有鲜明的空间特征，以及主体在做决策时是否考虑空间因素）。主体的行为通常受到'''中间件 Middleware''' 的调控。中间件使得人们可以管理可用资源、调控主体，极大地方便了人们对于多主体系统进行抽象设计。
* Decentralization: no agent is designated as controlling (or the system is effectively reduced to a monolithic system)<ref>{{cite journal |first1=Liviu |last1=Panait |first2=Sean |last2=Luke |url=http://cs.gmu.edu/~eclab/papers/panait05cooperative.pdf|title=Cooperative Multi-Agent Learning: The State of the Art |journal=Autonomous Agents and Multi-Agent Systems |volume=11 |issue=3 |pages=387–434 |year=2005 |doi=10.1007/s10458-005-2631-2|citeseerx=10.1.1.307.6671 }}</ref>
* Decentralization: no agent is designated as controlling (or the system is effectively reduced to a monolithic system)<ref>{{cite journal |first1=Liviu |last1=Panait |first2=Sean |last2=Luke |url=http://cs.gmu.edu/~eclab/papers/panait05cooperative.pdf|title=Cooperative Multi-Agent Learning: The State of the Art |journal=Autonomous Agents and Multi-Agent Systems |volume=11 |issue=3 |pages=387–434 |year=2005 |doi=10.1007/s10458-005-2631-2|citeseerx=10.1.1.307.6671 }}</ref>
* 自主性：主体至少是部分独立的，可以自我感知。
* 自主性：主体至少是部分独立的，可以自我感知、自主行动。
* 局部视野：没有一个主体可以掌握系统的全貌，或者由于系统十分复杂，没有一个主体可以利用全局性的知识。
* 局部视野：没有一个主体可以掌握系统的全貌，或者由于系统十分复杂，没有一个主体可以利用全局性的知识。
Multi-agent systems can manifest self-organisation as well as self-direction and other control paradigms and related complex behaviors even when the individual strategies of all their agents are simple. When agents can share knowledge using any agreed language, within the constraints of the system's communication protocol, the approach may lead to a common improvement. Example languages are Knowledge Query Manipulation Language (KQML) or Agent Communication Language (ACL).
Multi-agent systems can manifest self-organisation as well as self-direction and other control paradigms and related complex behaviors even when the individual strategies of all their agents are simple. When agents can share knowledge using any agreed language, within the constraints of the system's communication protocol, the approach may lead to a common improvement. Example languages are Knowledge Query Manipulation Language (KQML) or Agent Communication Language (ACL).
即使所有单个主体的策略都很简单，多主体系统也可以表现出自组织、自引导等控制范式以及相关的复杂行为。当主体之间可以在系统通信规范的约束下使用一些约定的语言来共享信息时，这种方法可能带来主体间的共赢。'''知识查询操作语言'''（英文：'''Knowledge Query Manipulation Language'''，简称'''KQML'''）'''和主体通信语言'''（英文：'''Agent Communication Language'''，简称'''ACL'''）是这类语言中的两个典型例子。
即使所有单个主体的策略都很简单，多主体系统也可以表现出自组织、自引导等控制范式以及相关的复杂行为。当主体之间可以在系统通信规范的约束下使用一些约定的语言来共享信息时，这种方法可能带来主体间的共赢。'''知识查询操作语言''' '''Knowledge Query Manipulation Language'''和主体通信语言''' '''Agent Communication Language'''是这类语言中的两个典型例子。
* 首先，一个主体将一个“谁可以...？”形式的请求分发出去。
* 首先，一个主体将一个“谁可以...？”形式的请求分发出去。
* 其次，与该请求相关的主体会响应道：“我可以，价格是...”。
* 其次，与该请求相关的主体会响应道：“我可以，前提是...”。
--~~这个价格是不是可以再想想 比如代价费用之类的？ 只是个人想法 不改也可以
--~~这个价格是不是可以再想想 比如代价费用之类的？ 只是个人想法 不改也可以
MAS tend to find the best solution for their problems without intervention. There is high similarity here to physical phenomena, such as energy minimizing, where physical objects tend to reach the lowest energy possible within the physically constrained world. For example: many of the cars entering a metropolis in the morning will be available for leaving that same metropolis in the evening.
MAS tend to find the best solution for their problems without intervention. There is high similarity here to physical phenomena, such as energy minimizing, where physical objects tend to reach the lowest energy possible within the physically constrained world. For example: many of the cars entering a metropolis in the morning will be available for leaving that same metropolis in the evening.
多主体系统常常可以在没有干预的情况下为它们的问题找到最好的解决方案，这与物理现象有很高的相似性。比如在能量最小化的例子中，物理主体倾向于在物理条件约束的世界中达到可能的最低能量。
The systems also tend to prevent propagation of faults, self-recover and be fault tolerant, mainly due to the redundancy of components.
The systems also tend to prevent propagation of faults, self-recover and be fault tolerant, mainly due to the redundancy of components.
Also, Multi-agent Systems Artificial Intelligence (MAAI) are used for simulating societies, the purpose thereof being helpful in the fields of climate, energy, epidemiology, conflict management, child abuse, .... Some organisations working on using multi-agent system models include Center for Modelling Social Systems, Centre for Research in Social Simulation, Centre for Policy Modelling, Society for Modelling and Simulation International.
Also, Multi-agent Systems Artificial Intelligence (MAAI) are used for simulating societies, the purpose thereof being helpful in the fields of climate, energy, epidemiology, conflict management, child abuse, .... Some organisations working on using multi-agent system models include Center for Modelling Social Systems, Centre for Research in Social Simulation, Centre for Policy Modelling, Society for Modelling and Simulation International.
此外，'''多主体系统人工智能'''(MAAI)被用于模拟社会，以助力气候，能源，流行病学，冲突管理，儿童虐待等方面的工作。一些致力于使用多主体系统模型的组织包括社会系统建模中心(Center for Modelling Social Systems)、社会模拟研究中心(Centre for Research in Social Simulation)、政策建模中心(Centre for Policy Modelling)以及国际建模与模拟学会(Society for Modelling and Simulation International)。
此外，'''多主体系统人工智能''' '''MAAI''' 被用于模拟社会，以助力气候，能源，流行病学，冲突管理，儿童虐待等方面的工作。一些致力于使用多主体系统模型的组织包括'''社会系统建模中心 Center for Modelling Social Systems'''、'''社会模拟研究中心 Centre for Research in Social Simulation'''、'''政策建模中心 Centre for Policy Modelling'''以及'''国际建模与模拟学会 Society for Modelling and Simulation International'''。
== See also 参见 ==
== See also 参见 ==