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Journal articles on the topic 'Agent'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Aprilia, Dita, Yusrizal Yusrizal, and Wahyu Syarvina. "Analisis Tingkat Literasi Keuangan Agen Asuransi Syariah di PT. Bumiputera 1912 Medan." Jurnal Manajemen Akuntansi (JUMSI) 3, no. 1 (2023): 303–16. http://dx.doi.org/10.36987/jumsi.v3i1.4026.

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This study aims to determine and analyze agent knowledge, agent behavior and agent attitudes towards sharia insurance at PT Bumiputera 1912 Medan. The research method used is a qualitative method used by researchers, namely primary, including distributing questionnaires to interview agents at PT Bumiputera 1912 Medan. Based on the research results obtained regarding the analysis of the level of financial literacy of Islamic insurance agents, namely, even though the knowledge level of Islamic insurance agents is in the moderate category or sufficiently understanding, the knowledge level of Isla

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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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SUMANTH REDDY, SHIVA. "AI Agents: Agent GPT." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem50557.

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Abstract - Agent GPT is an advanced autonomous AI system designed to simulate human-like reasoning and task execution through the deployment of AI agents. Unlike traditional large language models that respond passively to user prompts, Agent GPT can plan, iterate, and execute multi-step goals with minimal human intervention. Each agent operates based on a defined objective, breaking it down into smaller tasks, leveraging APIs, tools, or internet access to gather information, and adapting dynamically to changing conditions. The system is often built on top of language models such as GPT-4, and

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ANDREWS, RUSSELL J. "Neuroprotective "Agents" in Surgery: Secret "Agent" Man, or Common "Agent" Machine?" Annals of the New York Academy of Sciences 890, no. 1 NEUROPROTECTI (1999): 59–72. http://dx.doi.org/10.1111/j.1749-6632.1999.tb07981.x.

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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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Houghton, P. "16 Targeted agent with targeted agents." European Journal of Cancer Supplements 2, no. 8 (2004): 8–9. http://dx.doi.org/10.1016/s1359-6349(04)80025-9.

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Plaza, Enric, Josep Llu�s Arcos, Pablo Noriega, and Carles Sierra. "Competing agents in agent-mediated institutions." Personal Technologies 2, no. 3 (1998): 212–20. http://dx.doi.org/10.1007/bf01321177.

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8

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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XU, HAIPING, ZHIGUO ZHANG, and SOL M. SHATZ. "A SECURITY BASED MODEL FOR MOBILE AGENT SOFTWARE SYSTEMS." International Journal of Software Engineering and Knowledge Engineering 15, no. 04 (2005): 719–46. http://dx.doi.org/10.1142/s0218194005002518.

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Security modeling for agents has been one of the most challenging issues in developing practical mobile agent software systems. In the past, researchers have developed mobile agent systems with emphasis either on protecting mobile agents from malicious hosts or protecting hosts from malicious agents. In this paper, we propose a security based mobile agent system architecture that provides a general solution to protecting both mobile agents and agent hosts in terms of agent communication and agent migration. We present a facilitator agent model that serves as a middleware for secure agent commu

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GUAN, SHENG-UEI, and FANGMING ZHU. "AGENT FABRICATION AND ITS IMPLEMENTATION FOR AGENT-BASED ELECTRONIC COMMERCE." International Journal of Information Technology & Decision Making 01, no. 03 (2002): 473–89. http://dx.doi.org/10.1142/s0219622002000300.

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In the last decade, agent-based e-commerce has emerged as a potential role for the next generation of e-commerce. How to create agents for e-commerce applications has become a serious consideration in this field. This paper proposes a new scheme named agent fabrication and elaborates its implementation in multi-agent systems based on the SAFER (Secure Agent Fabrication, Evolution and Roaming) architecture. First, a conceptual structure is proposed for software agents carrying out e-commerce activities. Furthermore, agent module suitcase is defined to facilitate agent fabrication. With these de

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Wang, Wanyue. "Research on surface-active agent type PET antistatic agent." Applied and Computational Engineering 136, no. 1 (2025): 27–33. https://doi.org/10.54254/2755-2721/2025.21029.

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Surface-active agent type PET antistatic agent is a research hot spot in the field of antistatic materials in recent years, widely used in textile, packaging and electronic industries. PET (polyethylene terephthalate) is a polymer material with excellent properties, but its high electrical resistivity and tendency to accumulate static electricity limit its application in specific fields. Surface-active agent type antistatic agent can form a conductive layer on the surface of PET material through surface activation, effectively reducing static buildup and enhancing antistatic performance. Start

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Lou, Xingzhou, Junge Zhang, Timothy J. Norman, Kaiqi Huang, and Yali Du. "TAPE: Leveraging Agent Topology for Cooperative Multi-Agent Policy Gradient." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 16 (2024): 17496–504. http://dx.doi.org/10.1609/aaai.v38i16.29699.

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Multi-Agent Policy Gradient (MAPG) has made significant progress in recent years. However, centralized critics in state-of-the-art MAPG methods still face the centralized-decentralized mismatch (CDM) issue, which means sub-optimal actions by some agents will affect other agent's policy learning. While using individual critics for policy updates can avoid this issue, they severely limit cooperation among agents. To address this issue, we propose an agent topology framework, which decides whether other agents should be considered in policy gradient and achieves compromise between facilitating co

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13

Paetzke, Hans-Henning. "Agent der Menschlichkeit." osteuropa 69, no. 12 (2019): 139–56. http://dx.doi.org/10.35998/oe-2019-0060.

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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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Sajid, Qandeel, Ryan Luna, and Kostas Bekris. "Multi-Agent Pathfinding with Simultaneous Execution of Single-Agent Primitives." Proceedings of the International Symposium on Combinatorial Search 3, no. 1 (2021): 88–96. http://dx.doi.org/10.1609/socs.v3i1.18243.

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Multi-agent pathfinding is a challenging combinatorial problem that involves multiple agents moving on a graph from a set of initial nodes to a set of desired goals without inter-agent collisions. Searching the composite space of all agents has exponential complexity and does not scale well. Decoupled methods are more efficient but are generally incomplete. There are, however, polynomial time algorithms, which utilize single or few-agents primitives with completeness guarantees. One limitation of these alternatives is that the resulting solution is sequential, where only one agent moves at a t

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Matsui, Tetsuya, and Atsushi Koike. "Who Is to Blame? The Appearance of Virtual Agents and the Attribution of Perceived Responsibility." Sensors 21, no. 8 (2021): 2646. http://dx.doi.org/10.3390/s21082646.

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Virtual agents have been widely used in human-agent collaboration work. One important problem with human-agent collaboration is the attribution of responsibility as perceived by users. We focused on the relationship between the appearance of a virtual agent and the attribution of perceived responsibility. We conducted an experiment with five agents: an agent without an appearance, a human-like agent, a robot-like agent, a dog-like agent, and an angel-like agent. We measured the perceived agency and experience for each agent, and we conducted an experiment involving a sound-guessing game. In th

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Ruan, Jingqing, Linghui Meng, Xuantang Xiong, Dengpeng Xing, and Bo Xu. "Learning Multi-Agent Action Coordination via Electing First-Move Agent." Proceedings of the International Conference on Automated Planning and Scheduling 32 (June 13, 2022): 624–28. http://dx.doi.org/10.1609/icaps.v32i1.19850.

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Learning to coordinate actions among agents is essential in complicated multi-agent systems. Prior works are constrained mainly by the assumption that all agents act simultaneously, and asynchronous action coordination between agents is rarely considered. This paper introduces a bi-level multi-agent decision hierarchy for coordinated behavior planning. We propose a novel election mechanism in which we adopt a graph convolutional network to model the interaction among agents and elect a first-move agent for asynchronous guidance. We also propose a dynamically weighted mixing network to effectiv

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Farooq, Muhammad Omer, and Thomas Kunz. "Combining Supervised and Reinforcement Learning to Build a Generic Defensive Cyber Agent." Journal of Cybersecurity and Privacy 5, no. 2 (2025): 23. https://doi.org/10.3390/jcp5020023.

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Sophisticated mechanisms for attacking computer networks are emerging, making it crucial to have equally advanced mechanisms in place to defend against these malicious attacks. Autonomous cyber operations (ACOs) are considered a potential solution to provide timely defense. In ACOs, an agent that attacks the network is called a red agent, while an agent that defends against the red agent is called a blue agent. In real-world scenarios, different types of red agents can attack a network, requiring blue agents to defend against a variety of red agents, each with unique attack strategies and goal

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Sitepu, Novi Indriyani, and Saparuddin Siregar. "IMPROVING THE QUALITY OF SHARIA INSURANCE AGENTS THROUGH TECHNOLOGY OPTIMALIZATION AS A SHARIA-BASED MARKETING MEDIUM." At-tijaroh: Jurnal Ilmu Manajemen dan Bisnis Islam 7, no. 1 (2021): 15–29. http://dx.doi.org/10.24952/tijaroh.v7i1.3093.

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The physical, the intellectual and the spiritual qualities of the agent is creates agent competence so that they can compete in the sharia insurance marketing business. Competition for human performance is currently over helmed by the ease of technology through the internet mediawhich poses a challenge for agents to be able to take advantage of technology. The high competition needs to be framed using sharia views in order to maintain Islamic values. This phenomenon then makes insurance agents as a technology driver in marketing the shariah insurance business in sharia companies in the Nort Su

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Fan, Dongyu, Haikuo Shen, and Lijing Dong. "Multi-Agent Distributed Deep Deterministic Policy Gradient for Partially Observable Tracking." Actuators 10, no. 10 (2021): 268. http://dx.doi.org/10.3390/act10100268.

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In many existing multi-agent reinforcement learning tasks, each agent observes all the other agents from its own perspective. In addition, the training process is centralized, namely the critic of each agent can access the policies of all the agents. This scheme has certain limitations since every single agent can only obtain the information of its neighbor agents due to the communication range in practical applications. Therefore, in this paper, a multi-agent distributed deep deterministic policy gradient (MAD3PG) approach is presented with decentralized actors and distributed critics to real

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21

Foster, Jared, Boris Freidlin, E. L. Korn, and Malcolm Smith. "Evaluation of the contribution of randomised cancer clinical trials evaluating agents without documented single-agent activity." ESMO Open 5, no. 5 (2020): e000871. http://dx.doi.org/10.1136/esmoopen-2020-000871.

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BackgroundWith the development of targeted agents, the approach to combination cancer therapy has evolved to focus on identifying ways in which pathway inhibition by one agent may enhance the activity of other agents. In theory, this implies that under this new paradigm, agents are no longer required to show single-agent activity, as the pathway inhibited by the targeted agent may only have a therapeutic effect when given with other agents. This raises the question of the extent to which anticancer agents without single-agent activity can contribute to effective combination regimens.Patients a

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22

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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23

Bosse, Stefan. "Industrial Agents and Distributed Agent-Based Learning." Proceedings 1, no. 2 (2016): 14. http://dx.doi.org/10.3390/casa-3-s2004.

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Li, Jiaoyang, Pavel Surynek, Ariel Felner, Hang Ma, T. K. Satish Kumar, and Sven Koenig. "Multi-Agent Path Finding for Large Agents." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 7627–34. http://dx.doi.org/10.1609/aaai.v33i01.33017627.

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Multi-Agent Path Finding (MAPF) has been widely studied in the AI community. For example, Conflict-Based Search (CBS) is a state-of-the-art MAPF algorithm based on a twolevel tree-search. However, previous MAPF algorithms assume that an agent occupies only a single location at any given time, e.g., a single cell in a grid. This limits their applicability in many real-world domains that have geometric agents in lieu of point agents. Geometric agents are referred to as “large” agents because they can occupy multiple points at the same time. In this paper, we formalize and study LAMAPF, i.e., MAP

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Chiariglione, Leonardo, Masahiro Shibata, and Yeun-Bae Kim. "Agent Software Technologies. Standardization of Communicating Agents." Journal of the Institute of Image Information and Television Engineers 52, no. 4 (1998): 452–56. http://dx.doi.org/10.3169/itej.52.452.

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26

Hanretty, Chris. "Agents and Patients: The Principal-Agent Perspective." European Political Science 9, no. 4 (2010): 481–87. http://dx.doi.org/10.1057/eps.2010.57.

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Clarke, Randolph. "Free Will, Agent Causation, and “Disappearing Agents”." Noûs 53, no. 1 (2017): 76–96. http://dx.doi.org/10.1111/nous.12206.

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Nelson, Kay M., Alex Kogan, Rajendra P. Srivastava, Miklos A. Vasarhelyi, and Hai Lu. "Virtual auditing agents: the EDGAR Agent challenge." Decision Support Systems 28, no. 3 (2000): 241–53. http://dx.doi.org/10.1016/s0167-9236(99)00088-3.

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Voth, D. "Practical agents help out [virtual agent system." IEEE Intelligent Systems 20, no. 2 (2005): 4–6. http://dx.doi.org/10.1109/mis.2005.35.

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Li, Jiaoyang, Pavel Surynek, Ariel Felner, Hang Ma, T. K. Kumar, and Sven Koenig. "Multi-Agent Path Finding for Large Agents." Proceedings of the International Symposium on Combinatorial Search 10, no. 1 (2021): 186–87. http://dx.doi.org/10.1609/socs.v10i1.18483.

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Multi-Agent Path Finding (MAPF) has been widely studied in the AI community. For example, Conflict-Based Search (CBS) is a state-of-the-art MAPF algorithm based on a two-level tree-search. However, previous MAPF algorithms assume that an agent occupies only a single location at any given time, e.g., a single cell in a grid. This limits their applicability in many real-world domains that have geometric agents in lieu of point agents. Geometric agents are referred to as “large” agents because they can occupy multiple points at the same time. In this paper, we formalize and study LAMAPF, i.e., MA

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Vulis, Michael. "Agent/free agent newsreaders." Complexity 2, no. 2 (1996): 47–48. http://dx.doi.org/10.1002/(sici)1099-0526(199611/12)2:2<47::aid-cplx12>3.0.co;2-t.

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Elijah and Muhammad Naveed Dilber. "Complete Analysis of Fault Tolerance Schemes in Mobile Agents for a Reliable Mobile Agent Computation." Bonfring International Journal of Industrial Engineering and Management Science 7, no. 1 (2017): 20–24. http://dx.doi.org/10.9756/bijiems.8322.

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Du, Wei, Shifei Ding, Lili Guo, Jian Zhang, and Ling Ding. "Expressive Multi-Agent Communication via Identity-Aware Learning." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 16 (2024): 17354–61. http://dx.doi.org/10.1609/aaai.v38i16.29683.

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Information sharing through communication is essential for tackling complex multi-agent reinforcement learning tasks. Many existing multi-agent communication protocols can be viewed as instances of message passing graph neural networks (GNNs). However, due to the significantly limited expressive ability of the standard GNN method, the agent feature representations remain similar and indistinguishable even though the agents have different neighborhood structures. This further results in the homogenization of agent behaviors and reduces the capability to solve tasks effectively. In this paper, w

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Sharp, William H., and Marc M. Sebrechts. "Impact of Perceived Agent Expertise on Trust in Computer Agent Recommendations." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 64, no. 1 (2020): 1355–59. http://dx.doi.org/10.1177/1071181320641323.

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Computer agents are frequently anthropomorphized, giving them appearances and responses similar to humans. Research has demonstrated that users tend to apply social norms and expectations to such computer agents, and that people interact with computer agents in a similar fashion as they would another human. Perceived expertise has been shown to affect trust in human-human relationships, but the literature investigating how this influences trust in computer agents is limited. The current study investigated the effect of computer agent perceived level of expertise and recommendation reliability

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Sghir, Ines, Ines Ben Jaafar, and Khaled Ghédira. "A Multi-Agent Based Optimization Method for Combinatorial Optimization Problems." International Journal on Artificial Intelligence Tools 27, no. 05 (2018): 1850021. http://dx.doi.org/10.1142/s0218213018500215.

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This paper introduces a Multi-Agent based Optimization Method for Combinatorial Optimization Problems named MAOM-COP. In this method, a set of agents are cooperatively interacting to select the appropriate operators of metaheuristics using learning techniques. MAOM-COP is a flexible architecture, whose objective is to produce more generally applicable search methodologies. In this paper, the MAOM-COP explores genetic algorithm and local search metaheuristics. Using these metaheuristics, the decision-maker agent, the intensification agents and the diversification agents are seeking to improve t

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Dou, Lintao, Zhen Jia, and Jian Huang. "Solving large-scale multi-agent tasks via transfer learning with dynamic state representation." International Journal of Advanced Robotic Systems 20, no. 2 (2023): 172988062311624. http://dx.doi.org/10.1177/17298806231162440.

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Many research results have emerged in the past decade regarding multi-agent reinforcement learning. These include the successful application of asynchronous advantage actor-critic, double deep Q-network and other algorithms in multi-agent environments, and the more representative multi-agent training method based on the classical centralized training distributed execution algorithm QMIX. However, in a large-scale multi-agent environment, training becomes a major challenge due to the exponential growth of the state-action space. In this article, we design a training scheme from small-scale mult

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Chen, Jianming, Yawen Wang, Junjie Wang, et al. "Understanding Individual Agent Importance in Multi-Agent System via Counterfactual Reasoning." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 15 (2025): 15785–94. https://doi.org/10.1609/aaai.v39i15.33733.

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Explaining multi-agent systems (MAS) is urgent as these systems become increasingly prevalent in various applications. Previous work has provided explanations for the actions or states of agents, yet falls short in understanding the blackboxed agent’s importance within a MAS and the overall team strategy. To bridge this gap, we propose EMAI, a novel agent-level explanation approach that evaluates the individual agent’s importance. Inspired by counterfactual reasoning, a larger change in reward caused by the randomized action of agent indicates its higher importance. We model it as a MARL probl

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MÜLLER, JÖRG P. "Architectures and applications of intelligent agents: A survey." Knowledge Engineering Review 13, no. 4 (1999): 353–80. http://dx.doi.org/10.1017/s0269888998004020.

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The objective of this paper is twofold. In its first part, we survey the state of the art in research on agent architectures. The architecture of an agent describes its modules and capabilities, and how these operate together. We structure the field by investigating three important research threads, i.e. architectures for reactive agents, deliberative agents and interacting agents. Then we describe various hybrid approaches that reconcile these three threads, aiming at a combination of different features like reactivity, deliberation and the ability to interact with other agents. These approac

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Rahim, Tengku Nurulhuda Tengku Abd, Ma Stella Tabora Domingo, Mohamed Farid Noor Batcha, and Zalilah Abd Aziz. "Automated Exam Question Set Generator Using Utility Based Agent and Learning Agent." International Journal of Machine Learning and Computing 10, no. 1 (2020): 164–69. http://dx.doi.org/10.18178/ijmlc.2020.10.1.914.

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Dimitrov, Radoslav. "Simulation Modelling of Multi-Agent Logistics Model in AnyLogistix Environment." Science, Engineering and Education 9, no. 1 (2024): 75–82. http://dx.doi.org/10.59957/see.v9.i1.2024.10.

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This paper presents the supply chain as a complex logistics system analyzed in the AnyLogistix environment, which includes production centers, warehouses, distribution centers, suppliers, retailers or trade chains. Simulation modelling within scientific research, economic and social processes is presented as one method for creating an agent-based simulation model. The assigned software agents operate in the simulation context, according to a prescribed flowchart of a typical agent-based model. An analysis was made of the elements of the supply chain management system and their interaction acco

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Meneses, Alexis, Hamed Mahzoon, Yuichiro Yoshikawa, and Hiroshi Ishiguro. "Multiple Groups of Agents for Increased Movement Interference and Synchronization." Sensors 22, no. 14 (2022): 5465. http://dx.doi.org/10.3390/s22145465.

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We examined the influence of groups of agents and the type of avatar on movement interference. In addition, we studied the synchronization of the subject with the agent. For that, we conducted experiments utilizing human subjects to examine the influence of one, two, or three agents, as well as human or robot avatars, and finally, the agent moving biologically or linearly. We found the main effect on movement interference was the number of agents; namely, three agents had significantly more influence on movement interference than one agent. These results suggest that the number of agents is mo

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Yu, Miao. "The Extension of KQML Primitive in Large Database Operation." Applied Mechanics and Materials 263-266 (December 2012): 1515–18. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.1515.

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In Multi-Agent system, the communication among the Agents is the basic problem. The Agent communication language design, especially for large database operation, has been the important part for improving the Multi-Agent system performance. Based on the Multi-Agent large scale database operation, this paper extends the KQML's Primitive for Agents communication. The extended KQML's Primitive can improve the Agent communication performance and the database query performance.

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Palanca, Javier, Jaime Andres Rincon, Carlos Carrascosa, Vicente Javier Julian, and Andrés Terrasa. "Flexible Agent Architecture: Mixing Reactive and Deliberative Behaviors in SPADE." Electronics 12, no. 3 (2023): 659. http://dx.doi.org/10.3390/electronics12030659.

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Over the years, multi-agent systems (MAS) technologies have shown their usefulness in creating distributed applications focused on autonomous intelligent processes. For this purpose, many frameworks for supporting multi-agent systems have been developed, normally oriented towards a particular type of agent architecture (e.g., reactive or deliberative agents). It is common, for example, for a multi-agent platform supporting the BDI (Belief, Desire, Intention) model to provide this agent model exclusively. In most of the existing agent platforms, it is possible to develop either behavior-based a

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Nababan, Maxtulus Junedy, Herman Mawengkang, Tulus Tulus, and Sutarman Sutarman. "Hidden Markov Model to Optimize Coordination Relationship for Learning Behaviour." International Journal of Religion 5, no. 9 (2024): 459–69. http://dx.doi.org/10.61707/52exbt60.

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School communities interact dynamically, much like the agents in a multi-agent system. For coordinated action, relationships between agents in a multi-agent system must be handled. One technique for persuading individuals to behave in a coordinated manner is to manage the role of agents in generating knowledge, attitudes, and practices. Managing these connections is difficult due to the large number of unknowns. Modeling can aid in the clarification of agent relationships. Coordination mechanisms can be modeled using Markov models. Agents can demonstrate and consider how their actions affect o

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Zhang, Li, Zhi Qi, Hao Cui, Sen Hua Wang, Ya Hui Ning, and Qian Zhu Wang. "Exploring Agent-Based Modeling for Emergency Logistics Collaborative Decision Making." Advanced Materials Research 710 (June 2013): 781–85. http://dx.doi.org/10.4028/www.scientific.net/amr.710.781.

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Aiming at the requirements of urgency and dynamics in emergency logistics, this paper presents a multi-agent system (MAS) concept model for emergency logistics collaborative decision making. The suggested model includes three kinds of agents, i.e., role agent, function agent and assistant agent. Role agent excutes emergency logistics activities, function agent achieves the task requirements in every work phase and assistant agent helps organizing and visiting data. Two levels agent views serve as the basic skeleton of the MAS. Top level is the global decision-making view, which describes the t

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Yunchyk, Valentyna, Natalia Kunanets, Volodymyr Pasichnyk, and Anatolii Fedoniuk. "Analysis of Artificial Intellectual Agents for E-Learning Systems." Vìsnik Nacìonalʹnogo unìversitetu "Lʹvìvsʹka polìtehnìka". Serìâ Ìnformacìjnì sistemi ta merežì 10 (December 2021): 41–57. http://dx.doi.org/10.23939/sisn2021.10.041.

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The key terms and basic concepts of the agent are analyzed. The structured general classification of agents according to the representation of the model of the external environment, by the type of processing information and by the functions performed is given. The classification of artificial agents (intellectual, reflex, impulsive, trophic) also is s analyzed. The necessary conditions for the implementation of a certain behavior by the agent are given, as well as the scheme of functioning of the intelligent agent. The levels of knowledge that play a key role in the architecture of the agent a

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Botchkaryov, Alexey. "Multi-agent Coordination with Deferred Asynchronous Messaging in a Distributed Coordination Space." Advances in Cyber-Physical Systems 7, no. 2 (2022): 83–90. http://dx.doi.org/10.23939/acps2022.02.083.

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A method of multi-agent coordination with deferred asynchronous messaging in a distributed coordination space has been proposed. The method has been based on the concept of multi-agent conditional interaction. The method has used 1) a distributed coordination space in which agents move, 2) the rules of state transitions for the coordination space nodes depending on the movements of agents, 3) the rules of agents move and state transitions depending on the states of the coordination space nodes, 4) a multi-agent coordination game based on the coordination space and the rules. The coordination s

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Li, Xilun, Zhan Li, Xiaolong Zheng , Xuebo Yang , and Xinghu Yu . "The Study of Crash-Tolerant, Multi-Agent Offensive and Defensive Games Using Deep Reinforcement Learning." Electronics 12, no. 2 (2023): 327. http://dx.doi.org/10.3390/electronics12020327.

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In the multi-agent offensive and defensive game (ODG), each agent achieves its goal by cooperating or competing with other agents. The multi-agent deep reinforcement learning (MADRL) method is applied in similar scenarios to help agents make decisions. In various situations, the agents of both sides may crash due to collisions. However, the existing algorithms cannot deal with the situation where the number of agents reduces. Based on the multi-agent deep deterministic policy gradient (MADDPG) algorithm, we study a method to deal with a reduction in the number of agents in the training process

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Tang, Jin Peng, Ling Lin Li, Shu Kun Liu, De Peng Hu, Me Ling Cai, and Xiao Qiu Liu. "Research of Intersection Navigation Algorithm Based on Intelligent Agent." Applied Mechanics and Materials 641-642 (September 2014): 690–93. http://dx.doi.org/10.4028/www.scientific.net/amm.641-642.690.

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In order to improve the vehicle alone path finding way, put forward a kind of road navigation algorithm based on agent. First put forward the intelligent design method, and then the intelligent design is mapped to different kinds of the intelligent agents. And then expounds the function of operation control agent, agent, Lane agent and intersection agent needs to realize. Finally, based on these agents of the navigation algorithm is designed using Dijkstra algorithm.

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Jian, Yu Mei, and Ming Chen. "A Multi-Agent Cooperation System Structure for GWSN." Applied Mechanics and Materials 321-324 (June 2013): 523–27. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.523.

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According to the characteristics of GWSN, a Multi-Agent cooperation system structure of GWSN is put forward based on the complexity and changeableness of water area and biologic growth. In this structure, the Agent is divided into mobile Agent and static Agent. Static Agent is responsible for collecting data, and mobile Agent is responsible for move between clusters. Each cluster cooperation agents are responsible for data transmission and the data fusion process is divided into four levels. It manages greenhouse wireless measurement and control system by distributed agents’ information timely

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