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Multi-agent system

About: Multi-agent system is a research topic. Over the lifetime, 27978 publications have been published within this topic receiving 465191 citations. The topic is also known as: multi-agent systems & multiagent system.


Papers
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Book ChapterDOI
01 Jan 2005
TL;DR: A Process for Agent Societies Specification and Implementation (PASSI) is a step-by-step requirement-to-code methodology for designing and developing multi-agent societies, integrating design models and concepts from both object-oriented software engineering and artificial intelligence approaches using the UML notation.
Abstract: A Process for Agent Societies Specification and Implementation (PASSI) is a step-by-step requirement-to-code methodology for designing and developing multi-agent societies, integrating design models and concepts from both object-oriented (OO) software engineering and artificial intelligence approaches using the UML notation. The models and phases of PASSI encompass representation of system requirements, social viewpoint, solution architecture, code production and reuse, and deployment configuration supporting mobility of agents. The methodology is illustrated by the well-known Bookstore case study.

229 citations

ReportDOI
01 Jan 2005
TL;DR: An architecture is proposed that combines and integrates MACES and PMFserv to add validated agent behaviors to crowd simulations to expand the range of realistic human behaviors.
Abstract: : We describe a new architecture to integrate a psychological model into a crowd simulation system in order to obtain believable emergent behaviors. Our existing crowd simulation system (MACES) performs high level wayfinding to explore unknown environments and obtain a cognitive map for navigation purposes, in addition to dealing with low level motion within each room based on social forces. Communication and roles are added to achieve individualistic behaviors and a realistic way to spread information about the environment. To expand the range of realistic human behaviors, we use a system (PMFserv) that implements human behavior models from a range of ability, stress, emotion, decision theoretic and motivation sources. An architecture is proposed that combines and integrates MACES and PMFserv to add validated agent behaviors to crowd simulations.

227 citations

Journal ArticleDOI
TL;DR: A distributed swarm aggregation algorithm is developed for a team of multiple kinematic agents and it is shown that under the proposed control law, agents converge to a configuration where each agent is located at a bounded distance from each of its neighbors.
Abstract: A distributed swarm aggregation algorithm is developed for a team of multiple kinematic agents. Specifically, each agent is assigned a control law, which is the sum of two elements: a repulsive potential field, which is responsible for the collision avoidance objective, and an attractive potential field, which forces the agents to converge to a configuration where they are close to each other. Furthermore, the attractive potential field forces the agents that are initially located within the sensing radius of an agent to remain within this area for all time. In this way, the connectivity properties of the initially formed communication graph are rendered invariant for the trajectories of the closed-loop system. It is shown that under the proposed control law, agents converge to a configuration where each agent is located at a bounded distance from each of its neighbors. The results are also extended to the case of nonholonomic kinematic unicycle-type agents and to the case of dynamic edge addition. In the latter case, we derive a smaller bound in the swarm size than in the static case.

227 citations

Journal ArticleDOI
TL;DR: It is shown that most human decision sub-models are not explicitly based on a specific theory and if so they are mostly based on economic theories, such as the rational actor, and mainly ignoring other relevant disciplines.
Abstract: Recent reviews stated that the complex and context-dependent nature of human decision-making resulted in ad-hoc representations of human decision in agent-based land use change models (LUCC ABMs) and that these representations are often not explicitly grounded in theory. However, a systematic survey on the characteristics (e.g. uncertainty, adaptation, learning, interactions and heterogeneities of agents) of representing human decision-making in LUCC ABMs is missing. Therefore, the aim of this study is to inform this debate by reviewing 134 LUCC ABM papers. We show that most human decision sub-models are not explicitly based on a specific theory and if so they are mostly based on economic theories, such as the rational actor, and mainly ignoring other relevant disciplines. Consolidating and enlarging the theoretical basis for modelling human decision-making may be achieved by using a structural framework for modellers, re-using published decision models, learning from other disciplines and fostering collaboration with social scientists. Review on human decisions in agent-based models of land use change.Most human decision models are not based on theory.Used theories are mainly from economics and not from psychology.A framework to guide modellers how to implement human decision is needed.

226 citations

Journal Article
TL;DR: This article presents some of the critical notions in MASs and the research work that has addressed them, and organizes these notions around the concept of problem-solving coherence, which I believe is one of the most critical overall characteristics that an MAS should exhibit.
Abstract: Agent-based systems technology has generated lots of excitement in recent years because of its promise as a new paradigm for conceptualizing, designing, and implementing software systems. This promise is particularly attractive for creating software that operates in environments that are distributed and open, such as the internet. Currently, the great majority of agent-based systems consist of a single agent. However, as the technology matures and addresses increasingly complex applications, the need for systems that consist of multiple agents that communicate in a peer-to-peer fashion is becoming apparent. Central to the design and effective operation of such multiagent systems (MASs) are a core set of issues and research questions that have been studied over the years by the distributed AI community. In this article, I present some of the critical notions in MASs and the research work that has addressed them. I organize these notions around the concept of problem-solving coherence, which I believe is one of the most critical overall characteristics that an MAS should exhibit.

226 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023536
20221,212
2021849
20201,098
20191,079
20181,105