Formalization of Weak Emergence in Multiagent Systems
多智能体系统论文代写 odern systems are complex and composed of parts that are autonomous in their interactions. Due to several agents and interactions in a system
Venkata Sai Rohan Illindra
Department of Computer Science
University of Adelaide
a1776428@student.adelaide.edu.au
ABSTRACT
Modern systems are complex and composed of parts that are autonomous in their interactions. Due to several agents and interactions in a system, emergent behavior can be exhibited as either desirable or undesirable. As such, formalization is needed to identify the weak emergence in multi-systems.多智能体系统论文代写
Formalization is critical to evaluate each agent behavior and how they are affecting the overall results of the whole system. Simulation is considered one of the most effective approaches to getting emergence from a system. In this context, this paper describes the concept of formalization of weak emergence in multi-agent systems. It begins with a brief introduction which explains the motivation of the research. It then continues to explore the related works in the field of emergence in multi-agent systems. The following part critically analyzes the article by Zsabo and Meng Teo. The paper ends with the application of the concept of emergence in a games model. The researchers concluded that emergence in multi-agent systems is a fundamental field that tries to solve undesirable results in a complex system like AI, and hence, developers need to use to verify systems.
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摘要 多智能体系统论文代写
现代系统是复杂的，由在相互作用中自主的部分组成。由于系统中存在多个代理和相互作用，紧急行为可以表现为可取或不可取。因此，需要形式化来识别多系统中的弱涌现。
形式化对于评估每个代理行为以及它们如何影响整个系统的整体结果至关重要。模拟被认为是从系统中获得涌现的最有效方法之一。在此背景下，本文描述了多智能体系统中弱涌现的形式化概念。它首先是一个简短的介绍，解释了研究的动机。然后继续探索多智能体系统涌现领域的相关工作。以下部分批判性地分析了 Zsabo 和 Meng Teo 的文章。本文以涌现概念在博弈模型中的应用结束。研究人员得出结论，多智能体系统的出现是一个基本领域，它试图解决像人工智能这样的复杂系统中的不良结果，因此，开发人员需要使用来验证系统。
KEYWORDS
Multi-agent, emergent behavior, complex systems, simulation
ACM Reference Format:
Sai Rohan IV, In Research Essay for Modelling and Analysis of Complex System Assignment
Changes made
I changed the structure according to the template.多智能体系统论文代写
Also, changed inline references to [1] style
Stated the article to be analyzed in the introduction section
Added more information in the case study analysis
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关键词
多智能体、紧急行为、复杂系统、模拟
ACM 参考格式：
Sai Rohan IV，在复杂系统分配建模和分析的研究论文中
所做的更改
我根据模板更改了结构。
此外，将内联引用更改为 [1] 样式
在介绍部分陈述了要分析的文章
在案例研究分析中添加了更多信息
1.Introduction 多智能体系统论文代写
Traditionally, in system development, designers must have basic knowledge and purpose of the system as well as any other possible situation that may affect the system in the future [1]. The systems have little or no autonomy in operations because of future uncertainties [2]. As such, there is ever-grown system development due to complexities in systems in the bid to control the emergence of unintended usage or misuse. In computer science, it has motivated an increase in various techniques in software development.多智能体系统论文代写
Therefore, modern systems have many components that exhibit complex interplays and interconnections. Each of these agents is autonomous based on their internal logic. The complexity exists because of agent independence and interdependence [3]. Each of the agents in a system forms the component that is a functional unit. When a system is made, initially the developer has intended purpose. However, at the time of the system usage through the interaction of various agents, there might appear some issues in use or misuse by the agents, which were not intentioned by the developer. In this regard, this paper will analyze “Formalization of Weak Emergence in Multi-agent Systems” article by Claudia Szabo and Yong Meng Teo.
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一、简介 多智能体系统论文代写
传统上，在系统开发中，设计人员必须具备系统的基本知识和目的，以及未来可能影响系统的任何其他可能情况[1]。由于未来的不确定性，这些系统在操作上几乎没有自主权 [2]。因此，由于系统的复杂性，为了控制意外使用或误用的出现，系统开发不断发展。在计算机科学中，它推动了软件开发中各种技术的增加。
因此，现代系统具有许多表现出复杂相互作用和互连的组件。这些代理中的每一个都是基于其内部逻辑的自治。由于代理独立和相互依赖[3]，存在复杂性。系统中的每个代理构成作为功能单元的组件。当一个系统被制作出来时，最初开发者有预期的目的。但是，在系统使用时，通过各个代理的交互，可能会出现一些代理使用或误用的问题，这些问题并非开发者有意为之。对此，本文将分析 Claudia Szabo 和 Yong Meng Teo 的文章“Formalization of Weak Emergence in Multi-agent Systems”。
1.1 Motivation
When a human can use any deceptive mechanism to take advantage over others. They use pretense in performing a particular action or pretend not to know so as not to share. This is the aspect that is exhibited by autonomous agents in multi-agent systems. That the agents can have hidden actions, resources, or show decoy action to deceive. The paper will focus on evaluating agents and deception emergence in a game system. As such, there is a need to assess emergence in a traffic jam as various autonomous agents interact to get the solution.
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1.1 动机
当一个人可以使用任何欺骗机制来利用他人时。 他们在执行特定动作时使用假装或假装不知道以免分享。 这是多代理系统中自治代理所表现出的方面。 代理可以有隐藏的动作、资源，或显示诱饵动作来欺骗。 该论文将侧重于评估游戏系统中的代理和欺骗的出现。 因此，当各种自主代理交互以获得解决方案时，需要评估交通拥堵中的出现。
1.2 Related Work
Relationships and interactions between agents’ cause emergence. Multi-agents are components of a complex system which act dependently and independently [4]. Emergence is unexpected behavior in systems which might be negative or positive. Each agent is autonomous and has particular action and hence affects how the7y interact in a system. The aggregate interaction between multi-agents may cause emergence in the system.多智能体系统论文代写
Although emergence elicits significant concern from developers, there is no definite approach in evaluating the existence of emergence in the system. Szabo and Meng Tao well explore emergence in systems in their article “Formalization of Weak Emergence in Multiagent System” [5]. The report states that when the number of components, interactions, and connections increase, the level of system complexity also increases. Thus, the article view emergence from two points of views, including scientific and philosophical [5]. The distinction between the two depends on the perspective on understanding the behavior of the component where the philosophical emergence is subjective system behavior as opposed to the scientific definition. Hence, to identify emergence, a researcher can use variable based, event-based, and grammar-based approaches.
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1.2 相关工作
代理之间的关系和相互作用导致出现。多智能体是复杂系统的组成部分，它们依赖和独立地行动 [4]。出现是系统中的意外行为，可能是消极的或积极的。每个代理都是自主的并且具有特定的动作，因此会影响系统中的交互方式。多智能体之间的聚合交互可能会导致系统中出现。
尽管涌现引起了开发人员的极大关注，但没有明确的方法来评估系统中涌现的存在。 Szabo 和 Meng Tao 在他们的文章“Formalization of Weak Emergence in Multiagent System”[5] 中很好地探索了系统中的涌现。报告指出，当组件、交互和连接的数量增加时，系统复杂程度也会增加。于是，文章观点就出现了两个观点，包括科学的和哲学的[5]。两者之间的区别取决于理解组件行为的视角，其中哲学涌现是主观系统行为，而不是科学定义。因此，为了识别出现，研究人员可以使用基于变量、基于事件和基于语法的方法。
1.3 History of the Concept
The concept of emergence in multi-agents is not new. It was introduced in ancient Greeks where it was termed as “the whole before the parts” [6]. The Greeks believed that properties that do not arise from the addition of the behaviors of each component. Emergence is mainly found in complex systems. There is no generally accepted definition of the term emergence in complex systems.多智能体系统论文代写
In modern systems, emergence has gained much research owing complex systems in computer science and software engineering. Developers know the software and the intended use and application. However, there are situations that the software system may not function by the developer’s specifications in each of the components. Therefore, emergence has caused systems developments to be continuous to seal gaps likely to cause emergence.
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1.3 概念的历史
多智能体中出现的概念并不新鲜。 它是在古希腊人中引入的，在那里它被称为“整体在部分之前”[6]。 希腊人相信属性不是由每个组件的行为相加而产生的。 涌现主要出现在复杂系统中。 对于复杂系统中的涌现一词，没有普遍接受的定义。
在现代系统中，由于计算机科学和软件工程中的复杂系统，涌现得到了很多研究。 开发人员了解软件以及预期用途和应用程序。 但是，在某些情况下，软件系统可能无法按照开发人员在每个组件中的规范运行。 因此，涌现导致系统发展不断，以弥补可能导致涌现的差距。
2.Related Work
2.1 Emergence
According to Szabo and Meng Tao, emergence is defined in terms of science and philosophy [5]. Philosophically, emergence is a subjective “unexpected behavior in complex systems, the limitation of the observer’s knowledge, the tool employed, and the scale and level of abstraction under which the system is observed. On the other hand, scientific perspective view emergence as intrinsic to the system and an independent view of the system.多智能体系统论文代写
Thus, emergence is defined as irreducible properties of the whole system, which are associated with components that aggregate to form a system. Also, Burmaoglu, Sartenaer, and Porter defined emergence can be defined as the behavior in the process and during the reorganization process of a complex system [7]. Moreover, the phenomena have been defined as the appearance of novelty as well as something unpredictable, unexplainable, and cannot be described in its basic physical terms [8]. Overall, emergence phenomena are considered as the pattern in the results and identifiable in their rights in a complex system. Though identifiable with a system, it is neither predictable nor analyzable from the system.
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二、相关工作 多智能体系统论文代写
2.1 出现
根据 Szabo 和 Meng Tao 的说法，涌现是从科学和哲学的角度定义的 [5]。从哲学上讲，涌现是一种主观的“复杂系统中的意外行为、观察者知识的局限性、所使用的工具以及观察系统的抽象规模和水平。另一方面，科学视角将涌现视为系统固有的和系统的独立视图。
因此，涌现被定义为整个系统的不可约属性，这些属性与聚合形成系统的组件相关联。此外，Burmaoglu、Sartenaer 和 Porter 定义的涌现可以定义为复杂系统在过程中和重组过程中的行为[7]。此外，这些现象已被定义为新奇事物的出现以及一些不可预测、无法解释且无法用其基本物理术语来描述的事物 [8]。总体而言，涌现现象被认为是复杂系统中结果的模式和可识别的权利。虽然可以用系统识别，但它既不能从系统中预测也不能分析。
2.2 Multi-Agent Systems
Agents are autonomous components of a system and are adaptable to the environmental changes in the system [9]. A multi-agent system is made of various agents functioning as an independent component of the whole. Thus, a complex system constitutes agents that exist at the same time, share a resource, and interact with each other. In this context, a multi-agent system can be formalized in the interaction between agents.多智能体系统论文代写
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2.2 多代理系统
代理是系统的自治组件，可以适应系统中的环境变化[9]。 多智能体系统由作为整体独立组成部分的各种智能体组成。 因此，一个复杂的系统由同时存在、共享资源并相互交互的代理组成。 在这种情况下，多代理系统可以在代理之间的交互中形式化。
2.3 Inter-Relatedness Between the Concepts
Emergence is as a result of interaction between the various agents in the system [10]. Each agent acts in autonomy to achieve a particular result in the system. The results are considered as the aggregate of all agents’ actions, which are controlled by the environment. At the time of interaction, the actions of all agents can influence the results of the whole system [11]. That is, even though the agents’ actions are within the set environment, their actions may cause undesired results from the system. It can be explained by Lwhole – Lpart = Le, where the whole is the complex system, and the part is the action of each component in the system. The agent to agent action in a particular environment determines the whole result system, which might be desirable or undesirable according to the system specifications.多智能体系统论文代写
According to Szaba and Meng, emergence involves chaos and novelty.
Chaos is the type of interaction between different entities. For instance, people at a cocktail party represent different entities interacting randomly. The chaos emerges because there is no clear pattern or rules of interaction. In a cocktail party, there is no single culture that prevails. Thus, no one knows how close or far away to stand next to each other, when and whether to make eye contact or if it is good or wrong to use first or last name when addressing the other person.多智能体系统论文代写
In such a novel and more complex system, an emergent order will occur. The emergent is unexpected and happens magically. In a cocktail party anything can happen as a surprise, and every participant know where to hide or when to celebrate a happy birthday. According to them, the results of the whole is dependent on the complexity of the agent’s interactions, which is determined by the set of rules in the system. The interaction applies some rule and ignores others regarding agents’ interests.
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2.3 概念之间的相互关联
出现是系统中各种代理之间相互作用的结果[10]。每个代理都自主行动以在系统中实现特定结果。结果被视为所有代理行为的集合，这些行为受环境控制。在交互时，所有代理的动作都会影响整个系统的结果[11]。也就是说，即使代理的行为在设定的环境内，他们的行为也可能导致系统产生不希望的结果。可以用 Lwhole – Lpart = Le 来解释，其中整体是复杂的系统，部分是系统中每个组件的动作。特定环境中的代理行为决定了整个结果系统，根据系统规范，这可能是可取的或不可取的。
根据 Szaba 和 Meng 的说法，出现涉及混乱和新奇。
混沌是不同实体之间的交互类型。例如，鸡尾酒会上的人们代表随机交互的不同实体。混乱的出现是因为没有明确的交互模式或规则。在鸡尾酒会上，没有单一的文化盛行。因此，没有人知道彼此站在一起有多近或多远，何时以及是否进行眼神交流，或者在称呼对方时使用名字或姓氏是好是坏。多智能体系统论文代写
在这样一个新的、更复杂的系统中，会出现一个紧急的秩序。突发事件出乎意料并且神奇地发生。在鸡尾酒会上，任何事情都可能发生意外，每个参与者都知道该躲在哪里或何时庆祝生日快乐。根据他们的说法，整体的结果取决于代理交互的复杂性，这是由系统中的规则集决定的。交互应用了一些规则，而忽略了关于代理利益的其他规则。
3.Proposed Work 多智能体系统论文代写
3.1 Emergence Formalism
3.1.1 Varieties and Levels of Emergence
Emergence occurs at various levels, including weak and strong [12]. To understand whether emergence has occurred requires simulation of the system at both macro and micro levels. Strong emergence cannot be deduced even in principle following the low-level domain of the system while weak emergence is only unexpected, given the properties and principles of the low-level domain of the system [13]. A nominal level was introduced to show that a macro property in a system cannot exist in the micro properties. A strong emergence exists a philosophical perspective of the emergence and is strongly emergent concerning a low-level domain. Weak emergence exists in the scientific view of emergent emerge weakly concerning a low-level domain. Strong emergent has strong effects than weak emergence.多智能体系统论文代写
Therefore, in defining the strong and weak emergence require modeling the system in a multi-level hierarchy where rule and laws guide the interactions between agents [13]. Reason being, the interactions that lead to emergence are associated with the multi-level hierarchy. The whole system is referred to as the micro-level and the parts or agents that interact statically or dynamically at the lower level are referred to micro-level. The sub-systems at the micro-level can be viewed as systems on their own when looked at the causation factor and the shift between the various levels in the system. From the micro-level, the whole encapsulates the parts during interactions, as shown below.
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三、拟议工作 多智能体系统论文代写
3.1 紧急形式主义
3.1.1 出现的种类和水平
涌现发生在各个层面，包括弱和强 [12]。要了解是否出现了出现，需要在宏观和微观层面对系统进行模拟。即使在原则上遵循系统的低级域，也不能推导出强涌现，而鉴于系统低级域的属性和原理，弱涌现只是出乎意料的[13]。引入名义水平是为了表明系统中的宏观属性不能存在于微观属性中。强涌现存在于涌现的哲学视角，并且是关于低级域的强涌现。弱涌现存在于关于低层次领域的涌现弱涌现的科学观点中。强突现比弱突现具有更强的影响。
因此，在定义强和弱出现时需要在多级层次结构中对系统进行建模，其中规则和法律指导代理之间的交互 [13]。原因是，导致出现的交互与多级层次结构相关联。整个系统称为微观层次，在较低层次上静态或动态交互的部分或代理称为微观层次。从因果关系和系统中各个层次之间的转变来看，微观层次的子系统可以被视为独立的系统。从微观上看，整体在交互过程中封装了部分，如下图所示。
3.1.2 Characteristics of Emergence
Characterization on whether the change is emergent or not requires abstractions at the two levels of the system hierarchy [14]. That is the macro and micro level. The whole system is represented as Lwhole, while the aggregate of the agents in the system is presented as Lsum. Thus, system emergence state is the difference between the Lwhole – Lsum, which gives Le. Lwhole is the behavior of the system when the parts are not interacting, and Lsum is the sum of the parts’ behavior without interaction.多智能体系统论文代写
The system states are then measured when each agent n interactions are taken in aggregate and measured against the whole state of the system regarding the agent’s interactions. Through simulation, all possible states of the system are calculated for possible system states and to compare the state differences to get emergence. Emergence in a system is characterized by state-space and degree of interactions of agents in micro-level.
3.1.3 Managing Emergence Behaviors
Although defining emergence of a complex system is critical, there exist underlying issues [15]. First, finding the sum of all the individual agents’ behavior is challenging. Secondly, simulating the system to determine the emergence is time-consuming as it involves repetitive practice and abstraction of agents. Besides, a researcher is faced with forwarding and inverse problems. When the emergence is identified, the challenge is to find the cause depending on whether it is weak or strong emergence.多智能体系统论文代写
On the hand, emergence has been a significant concern in artificial intelligence. The concepts of self-organization where agents in the system learn through action can result in emergence of unintended learned behavior in the AI system. The phenomena of undesirable emergence have led to caution in the development of intelligent systems. As a control measure to emergence of undesirable behavior, developers have to carry out rigorous simulation of the system to test the probability of emergence particularly the strong emergence which might not be deductive by principle in the system.
3.1.4 Motivation
When a human can use any deceptive mechanism to take advantage over others. They use pretense in performing a particular action or pretend not to know so as not to share. This is the aspect that is exhibited by autonomous agents in multi-agent systems. That the agents can have hidden actions, resources, or show decoy action to deceive. The paper will focus on evaluating agents and deception emergence in a game system. As such, there is a need to assess emergence in a traffic jam as various autonomous agents interact to get the solution.多智能体系统论文代写
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3.1.2 涌现特征
关于变化是否紧急的表征需要在系统层次结构的两个级别进行抽象[14]。这就是宏观和微观层面。整个系统用Lwhole表示，系统中代理的聚合用Lsum表示。因此，系统涌现状态是Lwhole-Lsum之间的差值，它给出了Le。 Lwhole 是系统在部件不相互作用时的行为，Lsum 是部件没有相互作用时的行为总和。
然后，当每个代理 n 交互被汇总并针对系统的整个状态进行测量时，系统状态会被测量，关于代理的交互。通过仿真，计算出系统所有可能的状态，计算出可能的系统状态，并比较状态差异，得到突现。系统中的出现以状态空间和代理在微观层面上的交互程度为特征。
3.1.3 管理突发行为
尽管定义复杂系统的出现至关重要，但存在潜在问题[15]。首先，找到所有个体代理行为的总和是具有挑战性的。其次，模拟系统以确定出现是耗时的，因为它涉及代理的重复练习和抽象。此外，研究人员还面临着前向和逆向问题。当确定出现时，挑战是根据它是弱出现还是强出现来找到原因。
另一方面，涌现一直是人工智能的一个重要问题。系统中的代理通过行动学习的自组织概念可能导致人工智能系统中出现意外的学习行为。不希望出现的现象导致了智能系统开发的谨慎。作为对不良行为出现的控制措施，开发人员必须对系统进行严格的模拟，以测试出现的概率，特别是系统中原则上可能无法演绎的强出现。
3.1.4 动机
当一个人可以使用任何欺骗机制来利用他人时。他们在执行特定动作时使用假装或假装不知道以免分享。这是多代理系统中自治代理所表现出的方面。代理可以有隐藏的动作、资源，或显示诱饵动作来欺骗。该论文将侧重于评估游戏系统中的代理和欺骗的出现。因此，当各种自主代理交互以获得解决方案时，需要评估交通拥堵中的出现。
3.2Background and Overview
In this case, we consider the game and game encounter. In a competitive game, players compete against each other, which is interaction. The game competition is carried out by the defined rules, which is the strategy. The environment of the game defines what action each player can take [16]. Therefore, when agents take a particular action simultaneously, their actions are dependent on a combination of actions. The cumulative set of actions performed by all agents influence the environment to change. The phenomena of changing the environment as a result of certain cumulative actions by agents raise the question of how agents can influence the environment if they all want to maximize their utility. The appropriate action to take is dependent on the goal and the understanding of the actions that lead to emergent behavior. In this case, the agents have negotiated to achieve a position that is favorable to them.多智能体系统论文代写
From the game above, agent I and agent J have the goal of gi and gj, respectively. Each of the agents can perform or fail to act A and B, as shown below.
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3.2背景和概述
在这种情况下，我们考虑游戏和游戏遭遇。在竞技游戏中，玩家之间相互竞争，这就是互动。游戏比赛是按照既定的规则进行的，这就是策略。游戏环境定义了每个玩家可以采取的行动 [16]。因此，当代理同时采取特定行动时，他们的行动取决于行动的组合。所有代理执行的累积操作集会影响环境的变化。由于代理人的某些累积行为而改变环境的现象提出了一个问题，如果他们都想最大化他们的效用，他们如何影响环境。采取适当的行动取决于目标和对导致紧急行为的行动的理解。在这种情况下，代理人已经通过谈判获得了对他们有利的位置。
从上面的游戏中，代理 I 和代理 J 分别有 gi 和 gj 的目标。每个代理可以执行或不执行 A 和 B，如下所示。多智能体系统论文代写
3.3 System formalism
The system can be formalized about the actions of the two agents. Agent i can choose to perform action B, which will give a greater value. Hence, the action for agent i with high utility is dependent on action by agent B. However; agent j can hide his action but inform agent i will take action B, agent i may take action B that is delivering highest utility. Then, agent, i take action A, which gives utility zero for agent i. Hence,
Utility agents = (action A, action B)多智能体系统论文代写
3.4 Proposed Process for Emergence Identification
The system will be simulated repeatedly identify the emergence. Each of the agents will act independently and will be identified as i and j. Lsum and Lpart will be calculated from action A and B, and the divergence in results over time will be Le (emergence).
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3.3 系统形式主
该系统可以关于两个代理的动作进行形式化。 代理 i 可以选择执行操作 B，这将提供更大的价值。 因此，具有高效用的代理 i 的动作取决于代理 B 的动作。 代理 j 可以隐藏他的行为，但通知代理 i 将采取行动 B，代理 i 可能采取提供最高效用的行动 B。 然后，代理 i 采取行动 A，这使代理 i 的效用为零。 因此，
实用代理=（动作A，动作B）
3.4 突发事件识别的拟议流程
系统会反复模拟识别出现。 每个代理将独立行动，并被标识为 i 和 j。 Lsum 和 Lpart 将根据操作 A 和 B 计算，结果随时间的差异将是 Le（出现）。
4.Case Study Analysis 多智能体系统论文代写
4.1 Concept Explanation When Modelled in a Multi-Agent System
Szabo and Meng Tao introduce the concept of emergence as the primary trend in computer science. From the viewpoint of the agent in technologies, there exists interconnectedness, uncertainty in some functions, intelligence, and developer role of establishing the presence of emergence and determine whether is it beneficial or harmful. A system can be abstracted to various functions performed by the relationship between agents. An agent is independent and autonomous and hence has decision-making, control, and communication capabilities. Thus, when individual functions of agents are aggregated can result in equal or different results than the results of the sum of the whole system resulting in emergence.
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四、案例分析
4.1 在多智能体系统中建模时的概念解释
Szabo 和 Meng Tao 介绍了作为计算机科学主要趋势的涌现的概念。 从技术中的代理的角度来看，某些功能、智能和开发者角色存在相互关联性、不确定性，确定涌现的存在并确定它是有益的还是有害的。 一个系统可以抽象为由代理之间的关系执行的各种功能。 代理是独立和自主的，因此具有决策、控制和通信能力。 因此，当个体的个体功能被聚合时，可能导致与导致涌现的整个系统总和的结果相等或不同的结果。
4.1.1 Overview
The article proposes an automated approach for the identification of emergent trends in a system. It continues to show the benefit of the automated emergence identification system using theory and experimentation. Therefore, through the application of their system, they show that it reduces state-space through simulation of the rate of interaction between agents. In this regard, the article uses a grammar-based formalization and process. The approach is based on the abstraction of individual agents from the complexity of the system. As such, it seeks to reduce the state-space explosion as the system increase in size while the number of agents and interactions increase. Therefore, it proposes that to identify emergence using a grammar-based approach, Le is calculated as the emergence of state property.多智能体系统论文代写
Thus, Le = Lwhole –Lsum.
Where Lwhole is the all possible system state agent, the interaction of agents in a particular environment, Lsum, is the aggregation of all the actions of agents in the system.
The approach shows that the size of Lwhole depends on the rate of agent interactions and state transition rules by the developer. The phenomena can be explained using different rules modeling the traffic jam; that is, there is an entire system rule, or rules of interest while ignoring others.
The case uses a flock of bird model to explore emergence in a multi-agent system using a grammar-based approach.
The modeling uses the bottom-up approach to explain the flocking phenomena. In this case, the analysis begins with the behavior of each bird, which has a cumulative effect on the whole system of birds. Weak emergence is observed when birds are flocking together. For instance, a V-shaped is a physical property that emerges and allows a flock of birds to migrate than when each of them migrates by themselves easily.多智能体系统论文代写
The model of flocking is determined by the interaction between the birds by each bird take the path relative to its neighbor and hence, V-shaped phenomena. Thus, in such a multisystem, there are m various types of n agents, which are (L)linked to each other in an environment (E). Notably, each agent interacts with each other and with environment autonomously with a set of attributes. Therefore, agents change states depending on the values of attributes at a particular time. As such, bird interaction with each other and the environment regarding specific rules per bird in a particular behavior rule given by:
Rule(condition): Sij (t) in connection to Sij(t + 1)
The phenomena in flocking of bird are replicated the computer systems, especially artificial intelligence and software development. The developers are required to simulate the system multiple time to have a high probability of emergence occurring. In modern technology where AI is growing, determination of emergence is critical for any negative behavior in the system.多智能体系统论文代写
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4.1.1 概述
本文提出了一种自动方法来识别系统中的紧急趋势。它继续使用理论和实验显示自动紧急情况识别系统的好处。因此，通过他们系统的应用，他们表明它通过模拟代理之间的交互速率来减少状态空间。在这方面，文章使用了基于语法的形式化和过程。该方法基于从系统的复杂性中抽象出单个代理。因此，它试图随着系统规模的增加以及代理和交互数量的增加而减少状态空间爆炸。因此，它建议使用基于语法的方法识别涌现，将 Le 计算为状态属性的涌现。
因此，Le = Lwhole –Lsum。
其中 Lwhole 是所有可能的系统状态代理，特定环境中代理的交互 Lsum 是系统中代理的所有动作的聚合。
该方法表明，Lwhole 的大小取决于开发人员的代理交互率和状态转换规则。这些现象可以使用不同的交通拥堵模型来解释；也就是有一个完整的系统规则，或者说有兴趣的规则而忽略其他的。
该案例使用一群鸟模型，使用基于语法的方法探索多智能体系统中的出现。
该建模使用自下而上的方法来解释植绒现象。在这种情况下，分析从每只鸟的行为开始，这对整个鸟类系统具有累积影响。当鸟类聚集在一起时，观察到出现较弱。例如，V 形是一种物理特性，它出现并允许一群鸟类迁徙，而不是每只鸟类自己轻松迁徙。
蜂群模型是由每只鸟相对于其邻居走的路径决定的鸟之间的相互作用，因此，V 形现象。因此，在这样的多系统中，有多种类型的 n 个代理，它们在环境 (E) 中 (L) 相互链接。值得注意的是，每个代理通过一组属性自主地相互交互并与环境交互。因此，代理会根据特定时间的属性值更改状态。因此，鸟类之间的相互作用以及环境中关于每只鸟类在特定行为规则中的特定规则的情况如下：
规则（条件）：与 Sij(t + 1) 相关的 Sij (t)
鸟群的现象在计算机系统中被复制，特别是人工智能和软件开发。开发人员需要多次模拟系统，才有很高的出现概率。在人工智能不断发展的现代技术中，确定出现对于系统中的任何负面行为都至关重要。
4.1.2 Rules and Behaviors to Note
The flock of birds uses behavior exhibited when a group of birds is foraging. The bird model has three rules, which include separation, alignment, and cohesion. Separation is for the birds to avoid crowding, alignment means that the birds steer towards the direction of the neighbor, and cohesion is steering towards the average position of neighbor. The generally, determination of emergence is dependent on the assumptions that each agent is different from each other and act autonomously. The interaction between the agent is dependent on the environment set in the system and behavior rules.多智能体系统论文代写
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4.1.2 要注意的规则和行为
鸟群使用在一群鸟觅食时表现出的行为。 鸟类模型具有三个规则，包括分离、对齐和凝聚。 分离是为了避免鸟儿拥挤，对齐是指鸟儿向邻居的方向转向，凝聚是向邻居的平均位置转向。 一般而言，出现的确定取决于每个代理彼此不同并自主行动的假设。 代理之间的交互取决于系统中设置的环境和行为规则。
5.Conclusion
Agent-based systems are complex and need thorough knowledge to predict emergence at development and execution. There are various methods of formalizing emergence, but the most appropriate one is the grammar system. Emergence is affected by the number of interactions made by the agents in the system. Thus, the higher the interaction, the higher the possibility of emergence to occur in a system.
Acknowledgment
The authors wish to thank Luong Ba Linh for discussions about this work.多智能体系统论文代写
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五、结论
基于代理的系统很复杂，需要全面的知识来预测开发和执行时的出现。 形式化涌现的方法有很多种，但最合适的一种是语法系统。 出现受到系统中代理进行的交互次数的影响。 因此，相互作用越高，系统中出现的可能性就越大。
致谢
作者要感谢 Luong Ba Linh 对这项工作的讨论。
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