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第42行： − 多主体系统由智能体（Agent）及其环境组成。典型的多主体系统研究是指软件智能体。然而，多智能体系统空间站中的机器人、人类或者人类团队同样适用。一个多智能体系统可能包含组合的人-特工团队。+ − 第50行：
第49行： − 代理可以分为从简单到复杂的类型。类别包括:+ + + + + + + 第64行：
第69行： − 主体环境可以分为:+ + + + + + 第90行：
第100行： − 多智能体系统中的代理人有几个重要特征:+
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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智能体组成的计算系统。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'''（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。
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，一般被用于自然系统的研究中，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”（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。
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。
Agents can be divided into types spanning simple to complex. Categories include:
Agents can be divided into types spanning simple to complex. Categories include:
主体可以按照从简单到复杂的顺序分为如下几个类型:
* Passive agents<ref name=yoann2010>{{citation |first1=Yoann |last1=Kubera |first2=Philippe |last2=Mathieu |first3=Sébastien |last3=Picault |url=http://www.lifl.fr/SMAC/publications/pdf/aamas2010-everything.pdf |title=Everything can be Agent! |journal=Proceedings of the Ninth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'2010) |pages=1547–1548 |year=2010 }}</ref> or "agent without goals" (such as obstacle, apple or key in any simple simulation)
* Passive agents<ref name=yoann2010>{{citation |first1=Yoann |last1=Kubera |first2=Philippe |last2=Mathieu |first3=Sébastien |last3=Picault |url=http://www.lifl.fr/SMAC/publications/pdf/aamas2010-everything.pdf |title=Everything can be Agent! |journal=Proceedings of the Ninth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'2010) |pages=1547–1548 |year=2010 }}</ref> or "agent without goals" (such as obstacle, apple or key in any simple simulation)
* 被动主体，或者“没有目标的主体”（比如简单仿真中的障碍物、苹果或钥匙）
* Active agents<ref name=yoann2010/> with simple goals (like birds in flocking, or wolf–sheep in [[Lotka–Volterra|prey-predator model]])
* Active agents<ref name=yoann2010/> with simple goals (like birds in flocking, or wolf–sheep in [[Lotka–Volterra|prey-predator model]])
* 具有简单目标的主动主体（比如鸟群中的鸟、“捕食者与猎物”模型中的狼和羊）
* Cognitive agents (complex calculations)
* Cognitive agents (complex calculations)
* 认知主题（可以进行复杂的计算）
Agent environments can be divided into:
Agent environments can be divided into:
主体所处的环境可以分为:
* Virtual
* Virtual
* 虚拟的
* Discrete
* Discrete
* 离散的
* Continuous
* Continuous
* 连续的
The agents in a multi-agent system have several important characteristics:
The agents in a multi-agent system have several important characteristics:
多主体系统中的代理人有几个重要特征: