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.

Self-organization through bottom-up coalition formation

Abstract: We present a distributed approach to self-organization in a distributed sensor network. The agents in the system use a series of negotiations incrementally to form appropriate coalitions of sensor and processing resources.Since the system is cooperative, we have developed a range of protocols that allow the agents to share meta-level information before they allocate resources. On one extreme the protocols are based on local utility computations, where each agent negotiates based on its local perspective. From there, a continuum of additional protocols exists in which agents base decisions on marginal social utility, the combination of an agent's marginal utility and that of others. We present a formal framework that allows us to quantify how social an agent can be in terms of the set of agents that are considered and how the choice of a certain level affects the decisions made by the agents and the global utility of the organization.Our results show that by implementing social agents, we obtain an organization with a high global utility both when agents negotiate over complex contracts and when they negotiate over simple ones. The main difference between the two cases is mainly the rate of convergence. Our algorithm is incremental, and therefore the organization that evolves can adapt and stabilize as agents enter and leave the system.

Top-down vs bottom-up methodologies in multi-agent system design

Abstract: Traditionally, two alternative design approaches have been available to engineers: top-down and bottom-up. In the top-down approach, the design process starts with specifying the global system state and assuming that each component has global knowledge of the system, as in a centralized approach. The solution is then decentralized by replacing global knowledge with communication. In the bottom-up approach, on the other hand, the design starts with specifying requirements and capabilities of individual components, and the global behavior is said to emerge out of interactions among constituent components and between components and the environment. In this paper we present a comparative study of both approaches with particular emphasis on applications to multi-agent system engineering and robotics. We outline the generic characteristics of both approaches from the MAS perspective, and identify three elements that we believe should serve as criteria for how and when to apply either of the approaches. We demonstrate our analysis on a specific example of load balancing problem in robotics. We also show that under certain assumptions on the communication and the external environment, both bottom-up and top-down methodologies produce very similar solutions.

An Ambient Intelligence Based Multi-Agent System for Alzheimer Health Care

Abstract: This article describes ALZ-MAS; an Ambient Intelligence based multi-agent system aimed at enhancing the assistance and health care for Alzheimer patients. The system makes use of several context-aware technologies that allow it to automatically obtain information from users and the environment in an evenly distributed way, focusing on the characteristics of ubiquity, awareness, intelligence, mobility, etc., all of which are concepts defined by Ambient Intelligence.

Distributed Consensus Control of Multi-Agent Systems With Higher Order Agent Dynamics and Dynamically Changing Directed Interaction Topologies

Abstract: In 2005, Ren and Beard, under the network connectivity assumption that the union of the directed interaction graphs contains a spanning tree frequently enough, proposed a control protocol to solve the distributed consensus control problem for a multi-agent system with first order integrator agent dynamics. The consensus control protocol for second order systems proposed by the same authors, Ren and Beard, requires that the switching directed interaction graph has a spanning tree at every time instant to guarantee consensus. In this technical note, we propose a distributed consensus control protocol which extends the first order system results of Ren and Beard to agents represented by a general higher order controllable linear system, under the same network connectivity assumption that the union of the directed interaction graphs contains a spanning tree frequently enough. We show that the consensus can be achieved asymptotically by the group of agents under our proposed distributed control protocol. Simulation study illustrates the effectiveness of our proposed method.