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Artículos de revistas sobre el tema "Multi Agent Systems"

Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 25 de julio de 2025

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1

Gómez-Sanz, Jorge, and Juan Pavón. "Methodologies for Developing Multi-Agent Systems." JUCS - Journal of Universal Computer Science 10, no. (4) (2004): 359–74. https://doi.org/10.3217/jucs-010-04-0359.

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As agent technology has matured with the deployment of a variety of applications, particularly in open and dynamic environments such as the web, several methodologies and tools have been proposed to support software engineers during the development process of such systems. This article takes an overall look at representative agent-oriented methodologies by considering how they support specific agent-related concepts. This serves to identify areas in which this technology has shown its potential to solve new problems, e.g., the ability to manage complexity with an organizational perspective, go

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2

Dastani, Mehdi. "Programming multi-agent systems." Knowledge Engineering Review 30, no. 4 (2015): 394–418. http://dx.doi.org/10.1017/s0269888915000077.

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AbstractWith the significant advances in the area of autonomous agents and multi-agent systems in the last decade, promising technologies for the development and engineering of multi-agent systems have emerged. The result is a variety of agent-oriented programming languages, development frameworks, execution platforms, and tools that facilitate building and engineering of multi-agent systems. This paper provides an overview of the multi-agent programming research field and explains the aim and characteristics of various multi-agent programming languages and development frameworks. This overvie

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3

SCHWEITZER, FRANK, and MATTHEW E. TAYLOR. "EDITORIAL: AGENTS AND MULTI-AGENT SYSTEMS." Advances in Complex Systems 14, no. 02 (2011): iii—iv. http://dx.doi.org/10.1142/s0219525911003025.

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4

Julian, Vicente, and Vicente Botti. "Multi-Agent Systems." Applied Sciences 9, no. 7 (2019): 1402. http://dx.doi.org/10.3390/app9071402.

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With the current advance of technology, agent-based applications are becoming a standard in a great variety of domains such as e-commerce, logistics, supply chain management, telecommunications, healthcare, and manufacturing. Another reason for the widespread interest in multi-agent systems is that these systems are seen as a technology and a tool that helps in the analysis and development of new models and theories in large-scale distributed systems or in human-centered systems. This last aspect is currently of great interest due to the need for democratization in the use of technology that a

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5

Brafman, R. I., and M. Tennenholtz. "On Partially Controlled Multi-Agent Systems." Journal of Artificial Intelligence Research 4 (June 1, 1996): 477–507. http://dx.doi.org/10.1613/jair.318.

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Motivated by the control theoretic distinction between controllable and uncontrollable events, we distinguish between two types of agents within a multi-agent system: controllable agents, which are directly controlled by the system's designer, and uncontrollable agents, which are not under the designer's direct control. We refer to such systems as partially controlled multi-agent systems, and we investigate how one might influence the behavior of the uncontrolled agents through appropriate design of the controlled agents. In particular, we wish to understand which problems are naturally descri

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6

BRAZIER, F. M. T., C. M. JONKER, J. TREUR, and N. J. E. WIJNGAARDS. "DELIBERATIVE EVOLUTION IN MULTI-AGENT SYSTEMS." International Journal of Software Engineering and Knowledge Engineering 11, no. 05 (2001): 559–81. http://dx.doi.org/10.1142/s0218194001000670.

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Evolution of automated systems, in particular evolution of automated agents based on agent deliberation, is the topic of this paper. Evolution is not a merely material process, it requires interaction within and between individuals, their environments and societies of agents. An architecture for an individual agent capable of (1) deliberation about the creation of new agents, and (2) (run-time) creation of a new agent on the basis of this, is presented. The agent architecture is based on an existing generic agent model, and includes explicit formal conceptual representations of both design str

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7

ALONSO, EDUARDO, MARK D'INVERNO, DANIEL KUDENKO, MICHAEL LUCK, and JASON NOBLE. "Learning in multi-agent systems." Knowledge Engineering Review 16, no. 3 (2001): 277–84. http://dx.doi.org/10.1017/s0269888901000170.

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In recent years, multi-agent systems (MASs) have received increasing attention in the artificial intelligence community. Research in multi-agent systems involves the investigation of autonomous, rational and flexible behaviour of entities such as software programs or robots, and their interaction and coordination in such diverse areas as robotics (Kitano et al., 1997), information retrieval and management (Klusch, 1999), and simulation (Gilbert & Conte, 1995). When designing agent systems, it is impossible to foresee all the potential situations an agent may encounter and specify an agent

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8

JONG, STEVEN DE, KARL TUYLS, and KATJA VERBEECK. "Fairness in multi-agent systems." Knowledge Engineering Review 23, no. 2 (2008): 153–80. http://dx.doi.org/10.1017/s026988890800132x.

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AbstractMulti-agent systems are complex systems in which multiple autonomous entities, called agents, cooperate in order to achieve a common or personal goal. These entities may be computer software, robots, and also humans. In fact, many multi-agent systems are intended to operate in cooperation with or as a service for humans. Typically, multi-agent systems are designed assuming perfectly rational, self-interested agents, according to the principles of classical game theory. Recently, such strong assumptions have been relaxed in various ways. One such way is explicitly including principles d

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9

Park, Sankyu, Key-Sun Choi, and K. H. (Kane) Kim. "A Framework for Multi-Agent Systems with Multi-Modal User Interfaces in Distributed Computing Environments." International Journal of Software Engineering and Knowledge Engineering 07, no. 03 (1997): 351–69. http://dx.doi.org/10.1142/s0218194097000217.

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In current multi-agent systems, the user is typically interacting with a single agent at a time through relatively inflexible and modestly intelligent interfaces. As a consequence, these systems force the users to submit simplistic requests only and suffer from problems such as the low-level nature of the system services offered to users, the weak reusability of agents, and the weak extensibility of the systems. In this paper, a framework for multi-agent systems called the open agent architecture (OAA) which reduces such problems, is discussed. The OAA is designed to handle complex requests th

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10

Yamada, Kazuaki, Kumiyo Nakakoji, and Kanji Ueda. "A Mutli-agent Systems Approach to Analyze Online Community Activities(Multi-agent and Learning,Session: TP2-A)." Abstracts of the international conference on advanced mechatronics : toward evolutionary fusion of IT and mechatronics : ICAM 2004.4 (2004): 51. http://dx.doi.org/10.1299/jsmeicam.2004.4.51_3.

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11

Felcy Judith, P. "Leveraging Multi - Agent Systems for Efficient Grazing Management." International Journal of Science and Research (IJSR) 13, no. 6 (2024): 640–42. http://dx.doi.org/10.21275/sr24611203011.

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12

Olaru, Andrei, and Monica Pricope. "Multi-Modal Decentralized Interaction in Multi-Entity Systems." Sensors 23, no. 6 (2023): 3139. http://dx.doi.org/10.3390/s23063139.

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Current multi-agent frameworks usually use centralized, fixed communication infrastructures for the entities that are deployed using them. This decreases the robustness of the system but is less challenging when having to deal with mobile agents that can migrate between nodes. We introduce, in the context of the FLASH-MAS (Fast and Lightweight Agent Shell) multi-entity deployment framework, methods to build decentralized interaction infrastructures which support migrating entities. We discuss the WS-Regions (WebSocket Regions) communication protocol, a proposal for interaction in deployments u

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13

Jaleel, Hanan Qassim, Jane Jaleel Stephan, and Sinan A. Naji. "Multi-Agent Systems: A Review Study." Ibn AL- Haitham Journal For Pure and Applied Sciences 33, no. 3 (2020): 188. http://dx.doi.org/10.30526/33.3.2483.

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Multi-agent systems are subfield of Artificial Intelligence that has experienced rapid growth because of its flexibility and intelligence in order to solve distributed problems. Multi-agent systems (MAS) have got interest from various researchers in different disciplines for solving sophisticated problems by dividing them into smaller tasks. These tasks can be assigned to agents as autonomous entities with their private database, which act on their environment, perceive, process, retain and recall by using multiple inputs. MAS can be defined as a network of individual agents that share knowled

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14

Dushkin, Roman. "Multi-agent systems for cooperative ITS." Тренды и управление, no. 1 (January 2021): 42–50. http://dx.doi.org/10.7256/2454-0730.2021.1.34169.

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This article presents an original perspective upon the problem of creating intelligent transport systems in the conditions of using highly automated vehicles that freely move on the urban street-road networks. The author explores the issues of organizing a multi-agent system from such vehicles for solving the higher level tasks rather than by an individual agent (in this case &ndash; by a vehicle). Attention is also given to different types of interaction between the vehicles or vehicles and other agents. The examples of new tasks, in which the arrangement of such interaction would play a

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15

Flathmann, Christopher, Nathan McNeese, and Lorenzo Barberis Canonico. "Using Human-Agent Teams to Purposefully Design Multi-Agent Systems." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (2019): 1425–29. http://dx.doi.org/10.1177/1071181319631238.

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With multi-agent teams becoming more of a reality every day, it is important to create a common design model for multi-agent teams. These teams need to be able to function in dynamic environments and still communicate with any humans that may need a problem solved. Existing human-agent research can be used to purposefully create multi-agent teams that are interdependent but can still interact with humans. Rather than creating dynamic agents, the most effective way to overcome the dynamic nature of modern workloads is to create a dynamic team configuration, rather than individual member-agents

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16

Silva, Viviane Torres da, Fernanda Duran, José Guedes, and Carlos J. P. de Lucena. "Governing multi-agent systems." Journal of the Brazilian Computer Society 13, no. 2 (2007): 19–34. http://dx.doi.org/10.1590/s0104-65002007000200003.

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17

Mascardi, Viviana, Danny Weyns, and Alessandro Ricci. "Engineering Multi-Agent Systems." ACM SIGSOFT Software Engineering Notes 44, no. 1 (2019): 18–28. http://dx.doi.org/10.1145/3310013.3310035.

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Mascardi, Viviana, Danny Weyns, Alessandro Ricci, et al. "Engineering Multi-Agent Systems." ACM SIGSOFT Software Engineering Notes 44, no. 1 (2019): 18–28. http://dx.doi.org/10.1145/3310013.3322175.

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19

Mascardi, Viviana, Danny Weyns, and Alessandro Ricci. "Engineering Multi-Agent Systems." ACM SIGSOFT Software Engineering Notes 44, no. 1 (2019): 35. http://dx.doi.org/10.1145/3310013.3322181.

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20

da Silva, Viviane Torres, and Carlos J. P. de Lucena. "Modeling multi-agent systems." Communications of the ACM 50, no. 5 (2007): 103–8. http://dx.doi.org/10.1145/1230819.1241671.

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21

DASTANI, MEHDI, and JORGE J. GOMEZ-SANZ. "Programming multi-agent systems." Knowledge Engineering Review 20, no. 2 (2005): 151–64. http://dx.doi.org/10.1017/s0269888905000482.

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PROMAS (Programming Multi-Agent Systems) is an AgentLink technical forum that aims to bring together the researchers and practitioners from both academia and industry to discuss the problems related to the development of multi-agent systems and to evaluate the existing proposals and results. The specific focus of this technical forum is on agent-oriented programming languages and tools that can effectively and efficiently support the implementation of multi-agent systems. This paper provides an overview of the main contributions and conclusions derived from the first two editions of PROMAS tec

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22

Byrski, Aleksander, Rafał Dreżewski, Leszek Siwik, and Marek Kisiel-Dorohinicki. "Evolutionary multi-agent systems." Knowledge Engineering Review 30, no. 2 (2015): 171–86. http://dx.doi.org/10.1017/s0269888914000289.

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AbstractThe aim of this paper is to give a survey on the development and applications of evolutionary multi-agent systems (EMAS). The paper starts with a general introduction describing the background, structure and behaviour of EMAS. EMAS application to solving global optimisation problems is presented in the next section along with its modification targeted at lowering the computation costs by early removing certain agents based on immunological inspirations. Subsequent sections deal with the elitist variant of EMAS aimed at solving multi-criteria optimisation problems, and the co-evolutiona

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23

Camarinha-Matos, Luis M., Hamideh Afsarmanesh, and Vladimir Mařík. "Multi-agent systems applications." Robotics and Autonomous Systems 27, no. 1-2 (1999): 1–2. http://dx.doi.org/10.1016/s0921-8890(99)00006-8.

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24

da Silva, Viviane Torres, Fernanda Duran, José Guedes, and Carlos J. P. de Lucena. "Governing multi-agent systems." Journal of the Brazilian Computer Society 13, no. 2 (2007): 19–34. http://dx.doi.org/10.1007/bf03192407.

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25

Van Liedekerke, Marc H., and Nicholas M. Avouris. "Debugging multi-agent systems." Information and Software Technology 37, no. 2 (1995): 103–12. http://dx.doi.org/10.1016/0950-5849(95)93487-y.

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26

Lavendelis, Egons, and Janis Grundspenkis. "Design of Multi-Agent Based Intelligent Tutoring Systems." Scientific Journal of Riga Technical University. Computer Sciences 38, no. 38 (2009): 48–59. http://dx.doi.org/10.2478/v10143-009-0004-z.

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Design of Multi-Agent Based Intelligent Tutoring SystemsResearch of two fields, namely agent oriented software engineering and intelligent tutoring systems, have to be taken into consideration, during the design of multi-agent based intelligent tutoring systems (ITS). Thus there is a need for specific approaches for agent based ITS design, which take into consideration main ideas from both fields. In this paper we propose a top down design approach for multi-agent based ITSs. The proposed design approach consists of the two main stages: external design and internal design of agents. During the

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27

Cardoso, Rafael C., and Angelo Ferrando. "A Review of Agent-Based Programming for Multi-Agent Systems." Computers 10, no. 2 (2021): 16. http://dx.doi.org/10.3390/computers10020016.

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Intelligent and autonomous agents is a subarea of symbolic artificial intelligence where these agents decide, either reactively or proactively, upon a course of action by reasoning about the information that is available about the world (including the environment, the agent itself, and other agents). It encompasses a multitude of techniques, such as negotiation protocols, agent simulation, multi-agent argumentation, multi-agent planning, and many others. In this paper, we focus on agent programming and we provide a systematic review of the literature in agent-based programming for multi-agent

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28

Moskowitz, Ira S., Pi Rogers, and Stephen Russell. "Mutual Information and Multi-Agent Systems." Entropy 24, no. 12 (2022): 1719. http://dx.doi.org/10.3390/e24121719.

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We consider the use of Shannon information theory, and its various entropic terms to aid in reaching optimal decisions that should be made in a multi-agent/Team scenario. The methods that we use are to model how various agents interact, including power allocation. Our metric for agents passing information are classical Shannon channel capacity. Our results are the mathematical theorems showing how combining agents influences the channel capacity.

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29

YUAN, SOE-TSYR, and ZENG-LUNG WU. "AN INFRASTRUCTURE FOR ENGINEERING COOPERATIVE AGENTS." International Journal of Software Engineering and Knowledge Engineering 10, no. 06 (2000): 681–711. http://dx.doi.org/10.1142/s0218194000000377.

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Currently, systems of cooperative agents (multi-agent systems), possessing the capabilities of autonomy, adaptation, and cooperation, are being used in an increasingly wide variety of application areas, and the conversation-based multi-agent system design is the major design for those multi-agent systems. Supposedly, conversation-based multi-agent systems should have been prevailing enough for tackling dynamic aspects of problems in a variety of domains. However, for industries, multi-agent systems are still found to be in the birth stage where they only show their new values in anticipation f

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Anavankot, Amritha Menon, Stephen Cranefield, and Bastin Tony Roy Savarimuthu. "NEMAS: Norm Entrepreneurship in Multi-Agent Systems." Systems 12, no. 6 (2024): 187. http://dx.doi.org/10.3390/systems12060187.

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We propose a framework that integrates norm entrepreneurship from human society into the dynamics of an agent society. Most work in agent coordination in a distributed environment studies norms that are provided to agents as part of their specification or distributed from centralised agents. Exploring an alternate perspective, we focus on peer-to-peer interaction by providing the agents with the freedom to initiate norm creation in demanding situations like a potential interference. This paper explores the concept of norm entrepreneurship through proactive establishment and emergence of norms

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31

Li, Guangyu, Bo Jiang, Hao Zhu, Zhengping Che, and Yan Liu. "Generative Attention Networks for Multi-Agent Behavioral Modeling." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (2020): 7195–202. http://dx.doi.org/10.1609/aaai.v34i05.6209.

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Understanding and modeling behavior of multi-agent systems is a central step for artificial intelligence. Here we present a deep generative model which captures behavior generating process of multi-agent systems, supports accurate predictions and inference, infers how agents interact in a complex system, as well as identifies agent groups and interaction types. Built upon advances in deep generative models and a novel attention mechanism, our model can learn interactions in highly heterogeneous systems with linear complexity in the number of agents. We apply this model to three multi-agent sys

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32

Julian, Vicente, and Vicente Botti. "Special Issue on Multi-Agent Systems." Applied Sciences 13, no. 2 (2023): 1021. http://dx.doi.org/10.3390/app13021021.

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33

SHAKSHUKI, ELHADI, and SAAD ABU-DRAZ. "MULTI-AGENT SYSTEM ARCHITECTURE TO TRADING SYSTEMS." Journal of Interconnection Networks 06, no. 03 (2005): 283–302. http://dx.doi.org/10.1142/s0219265905001435.

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Agents for online trading purpose can be seen as a tool that helps computer users to purchase products from distributed resources based on their interests and preferences. One of the major features that determine the success of trading agent is the ability to negotiate with other agents, because most trading tasks involve interaction among agents. This paper presents a peer-to-peer multi-agent system architecture for online trading. The main objective of this system is to address some of the shortcomings that are present in contemporary online trading systems that focused on providing solution

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AHMAD, NAJLA, and ARVIN AGAH. "INTENT RECOGNITION IN MULTI-AGENT SYSTEMS: COW HERDING." International Journal of Pattern Recognition and Artificial Intelligence 28, no. 05 (2014): 1459006. http://dx.doi.org/10.1142/s021800141459006x.

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In a multi-agent system, an agent may utilize its idle time to assist other agents in the system. Intent recognition is proposed to accomplish this with minimal communication. An agent performing recognition observes the tasks other agents are performing and, unlike the much studied field of plan recognition, the overall intent of an agent is recognized instead of a specific plan. The observing agent may use capabilities that it has not observed. A conceptual framework is proposed for intent recognition systems. An implementation of the conceptual framework is tested and evaluated. We hypothes

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Ammar, Abdul Ameer Rasheed, Najm Abdullah Mohammed, and Sabah Al-Araji Ahmed. "A review of multi-agent mobile robot systems applications." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 4 (2022): 3517–29. https://doi.org/10.11591/ijece.v12i4.pp3517-3529.

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A multi-agent robot system (MARS) is one of the most important topics nowadays. The basic task of this system is based on distributive and cooperative work among agents (robots). It combines two important systems; multi-agent system (MAS) and multi-robots system (MRS). MARS has been used in many applications such as navigation, path planning detection systems, negotiation protocol, and cooperative control. Despite the wide applicability, many challenges still need to be solved in this system such as the communication links among agents, obstacle detection, power consumption, and collision avoi

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Peigné, Pierre, Mikolaj Kniejski, Filip Sondej, et al. "Multi-Agent Security Tax: Trading Off Security and Collaboration Capabilities in Multi-Agent Systems." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 26 (2025): 27573–81. https://doi.org/10.1609/aaai.v39i26.34970.

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As AI agents are increasingly adopted to collaborate on complex objectives, ensuring the security of autonomous multi-agent systems becomes crucial. We develop simulations of agents collaborating on shared objectives to study these security risks and security trade-offs. We focus on scenarios where an attacker compromises one agent, using it to steer the entire system toward misaligned outcomes by corrupting other agents. In this context, we observe infectious malicious prompts - the multi-hop spreading of malicious instructions. To mitigate this risk, we evaluated several strategies: two "vac

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37

Xu, Lü, Shuanghe Meng, and Liang Chen. "Consensus of Heterogeneous Multi-Agent Systems with Intermittent Communication." Journal of Systems Science and Information 5, no. 4 (2017): 328–42. http://dx.doi.org/10.21078/jssi-2017-328-15.

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AbstractThis paper studies consensus of a class of heterogeneous multi-agent systems composed of first-order and second-order agents with intermittent communication. For leaderless multi-agent systems, we propose a distributed consensus algorithm based on the intermittent information of neighboring agents. Some sufficient conditions are obtained to guarantee the consensus of heterogeneous multi-agent systems in terms of bilinear matrix inequalities (BMIs). Meanwhile, the relationship between communication duration and each control period is sought out. Moreover, the designed algorithm is exten

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Liu, Cong, Qiang Zhou, and Xiaoguang Hu. "Group consensus of heterogeneous multi-agent systems with fixed topologies." International Journal of Intelligent Computing and Cybernetics 8, no. 4 (2015): 294–311. http://dx.doi.org/10.1108/ijicc-03-2015-0009.

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Purpose – The purpose of this paper is to study the dynamical group consensus of heterogeneous multi-agent systems with fixed topologies. Design/methodology/approach – The tool used in this paper to model the topologies of multi-agent systems is algebraic graph theory. The matrix theory and stability theory are applied to research the group consensus of heterogeneous multi-agent systems with fixed topologies. The Laplace transform and Routh criterion are utilized to analyze the convergence properties of heterogeneous multi-agent systems. Findings – It is discovered that the dynamical group con

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Rohbogner, Gregor, Ulf Hahnel, Pascal Benoit, and Simon Fey. "Multi-agent systems’ asset for smart grid applications." Computer Science and Information Systems 10, no. 4 (2013): 1799–822. http://dx.doi.org/10.2298/csis130224072r.

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Multi-agent systems are a subject of continuously increasing interest in applied technical sciences. Smart grids are one evolving field of application. Numerous smart grid projects with various interpretations of multi-agent systems as new control concept arose in the last decade. Although several theoretical definitions of the term ?agent? exist, there is a lack of practical understanding that might be improved by clearly distinguishing the agent technologies from other state-of-the-art control technologies. In this paper we clarify the differences between controllers, optimizers, learning sy

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Quansheng, Liu, Xu Min, and Peng Li. "Distributed event-triggered scheme for discrete-time second-order multi-agent systems." Journal of Algorithms & Computational Technology 11, no. 1 (2016): 83–92. http://dx.doi.org/10.1177/1748301816665533.

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In order to achieve the consistency of multi-agent systems, each agent needs to communicate with its adjacent agents, which will consume energy of sensors embedded on the agents and occupy network bandwidth of multi-agent systems. Both resources are limited. To solve the above problem, a novel distributed event-triggered scheme of discrete-time second-order multi-agent systems are proposed in this article. The characteristics of the scheme have two aspects. Firstly, the event-triggered conditions are considered for the state and the velocity separately. Secondly, when the event is triggered on

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D'INVERNO, MARK, MICHAEL FISHER, ALESSIO LOMUSCIO, et al. "Formalisms for multi-agent systems." Knowledge Engineering Review 12, no. 3 (1997): 315–21. http://dx.doi.org/10.1017/s0269888997003068.

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As computer scientists, our goals are motivated by the desire to improve computer systems in some way: making them easier to design and implement, more robust and less prone to error, easier to use, faster, cheaper, and so on. In the field of multi-agent systems, our goal is to build systems capable of flexible autonomous decision making, with societies of such systems cooperating with one-another. There is a lot of formal theory in the area but it is often not obvious what such theories should represent and what role the theory is intended to play. Theories of agents are often abstract and ob

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Čavrak, Igor, Armin Stranjak, and Mario Žagar. "SDLMAS: A Scenario Modeling Framework for Multi-Agent Systems." JUCS - Journal of Universal Computer Science 15, no. (4) (2009): 898–925. https://doi.org/10.3217/jucs-015-04-0898.

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In this paper we analyze existing methods and languages for modeling agent interactions and propose a SDLMAS Framework for rapid design, development and runtime support of multi-agent systems. The framework provides a simple but expressive declarative language for modeling complex interactions among agents. Proposed language is based on scenarios, sequences of conversation actions directed towards achieving a goal. Scenario descriptions are converted into program code for a chosen target agent platform and system execution is supported by a runtime framework.

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Melo, Victor S., Alison R. Panisson, and Rafael H. Bordini. "Meta-Information and Argumentation in Multi-Agent Systems." iSys - Brazilian Journal of Information Systems 10, no. 3 (2017): 74–97. http://dx.doi.org/10.5753/isys.2017.347.

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In this work we compile our research regarding meta-information in multi-agent systems. In particular, we describe some agents profiles represent- ing different attitudes which describe how agents consider meta-information in their decisions-making and reasoning processes. Furthermore, we describe how we have combined different meta-information available in multi-agent systems with an argumentation-based reasoning mechanism. In our approach, agents are able to decide more conflicts between information/arguments, given that they are able to use different meta-information (often combined) to dec

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Kuznetsov, O. P. "Asynchronous Multi-Agent Multisorted Systems." Automation and Remote Control 82, no. 2 (2021): 294–307. http://dx.doi.org/10.1134/s0005117921020089.

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45

Monitor, I&S. "Multi-agent systems: Selected reading." Information & Security: An International Journal 8 (2002): 116–20. http://dx.doi.org/10.11610/isij.0807.

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46

Minsky, Naftaly. "Law-governed multi-agent systems." ACM SIGSOFT Software Engineering Notes 30, no. 4 (2005): 1. http://dx.doi.org/10.1145/1082983.1082965.

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47

Müller, Jean-Pierre, and H. Van Dyke Parunak. "Multi-Agent Systems and Manufacturing." IFAC Proceedings Volumes 31, no. 15 (1998): 545–50. http://dx.doi.org/10.1016/s1474-6670(17)40609-4.

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48

RAMCHURN, SARVAPALI D., DONG HUYNH, and NICHOLAS R. JENNINGS. "Trust in multi-agent systems." Knowledge Engineering Review 19, no. 1 (2004): 1–25. http://dx.doi.org/10.1017/s0269888904000116.

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Resumen

Trust is a fundamental concern in large-scale open distributed systems. It lies at the core of all interactions between the entities that have to operate in such uncertain and constantly changing environments. Given this complexity, these components, and the ensuing system, are increasingly being conceptualised, designed, and built using agent-based techniques and, to this end, this paper examines the specific role of trust in multi-agent systems. In particular, we survey the state of the art and provide an account of the main directions along which research efforts are being focused. In so do

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49

BINMORE, KEN, CRISTIANO CASTELFRANCHI, JAMES DORAN, and MICHAEL WOOLDRIDGE. "Rationality in Multi-Agent Systems." Knowledge Engineering Review 13, no. 3 (1998): 309–14. http://dx.doi.org/10.1017/s0269888998003026.

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50

Beer, Martin, Mark d'Inverno, Michael Luck, Nick Jennings, Chris Preist, and Michael Schroeder. "Negotiation in multi-agent systems." Knowledge Engineering Review 14, no. 3 (1999): 285–89. http://dx.doi.org/10.1017/s0269888999003021.

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