Topic
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.
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TL;DR: This paper presents a new and systematic procedure to design sub-optimal hierarchical feedback controllers for the leader-follower consensus problem in homogeneous multi-agent systems and demonstrates the effectiveness of the proposed method.
86 citations
TL;DR: A graph-theoretic characterization of controllability and observability of linear systems over finite fields shows that a linear system will be structurally controllable and observable over a finite field if the graph of the system satisfies certain properties, and the size of the field is sufficiently large.
Abstract: We develop a graph-theoretic characterization of controllability and observability of linear systems over finite fields. Specifically, we show that a linear system will be structurally controllable and observable over a finite field if the graph of the system satisfies certain properties, and the size of the field is sufficiently large. We also provide graph-theoretic upper bounds on the controllability and observability indices for structured linear systems (over arbitrary fields). We then use our analysis to design nearest-neighbor rules for multi-agent systems where the state of each agent is constrained to lie in a finite set. We view the discrete states of each agent as elements of a finite field, and employ a linear iterative strategy whereby at each time-step, each agent updates its state to be a linear combination (over the finite field) of its own state and the states of its neighbors. Using our results on structural controllability and observability, we show how a set of leader agents can use this strategy to place all agents into any desired state (within the finite set), and how a set of sink agents can recover the set of initial values held by all of the agents.
86 citations
TL;DR: The number of distributed energy components and devices continues to increase globally and as a result, distributed control schemes are desirable for managing and utilizing these devices, together with their applications.
Abstract: The number of distributed energy components and devices continues to increase globally. As a result, distributed control schemes are desirable for managing and utilizing these devices, together wit...
86 citations
01 Jun 2000
TL;DR: This paper addresses issues such as whether scalability is a theme that can be investigated in isolation to a particular agent development environment or application, and more importantly, whether metrics can be identified to compare the relative performance of multi-agent systems.
Abstract: Scalability is an issue that becomes important when developing practical software agent systems, to perform some of the applications that agent development tools identify. In this paper we address issues such as whether scalability is a theme that can be investigated in isolation to a particular agent development environment or application, and more importantly, whether metrics can be identified to compare the relative performance of multi-agent systems. Scalability is considered from a performance engineering perspective, with the additional constraint of trying to model both mobile and intelligent agents using the same techniques. Petri net based performance models are presented, which can be run on various publicly available simulators. We summarise approaches taken by different segments of the agents community, and use this to identify the disparity in what is termed as 'Scalability'. Our main contribution is to highlight the importance of combining performance engineering with agent oriented design methodologies, to design and build large agent based applications. Content Areas: agent-based software engineering, designing agent systems, lessons learned from deployed agents, multi-agent communication coordination and collaboration, organization
86 citations
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TL;DR: In this paper, the authors present a mathematical framework for COINs and investigate the real-world applicability of the core concepts of that framework via two computer experiments: they show that their framework performs near optimally in a difficult variant of the Arthur's bar problem and in particular avoid the tragedy of the commons for that problem.
Abstract: We consider the problem of how to design large decentralized multi-agent systems (MAS's) in an automated fashion, with little or no hand-tuning. Our approach has each agent run a reinforcement learning algorithm. This converts the problem into one of how to automatically set/update the reward functions for each of the agents so that the global goal is achieved. In particular we do not want the agents to ``work at cross-purposes'' as far as the global goal is concerned. We use the term artificial COllective INtelligence (COIN) to refer to systems that embody solutions to this problem. In this paper we present a summary of a mathematical framework for COINs. We then investigate the real-world applicability of the core concepts of that framework via two computer experiments: we show that our COINs perform near optimally in a difficult variant of Arthur's bar problem (and in particular avoid the tragedy of the commons for that problem), and we also illustrate optimal performance for our COINs in the leader-follower problem.
86 citations