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.

Leader-based multi-agent coordination: controllability and optimal control

Abstract: In this paper, we consider the situation where a collection of leaders dictate the motion of the followers in heterogenous multi-agent applications. In particular, the followers move according to a decentralized averaging rule, while the leaders' motion is unconstrained. Thus, the trajectories of the leaders can be viewed as exogenous control inputs, which allows us to state and study questions concerning controllability and optimal control.

Event-Triggered Communication for Leader-Following Consensus of Second-Order Multiagent Systems

Abstract: This paper is concerned with leader-following consensus of second-order multiagent systems with nonlinear dynamics. First, to save the limited communication resources, a new event-triggered control protocol is delicately developed without requiring continuous communication among the follower agents. Then, by employing the Lyapunov functional method and the Kronecker product technique, a novel sufficient criterion with less conservation is derived to guarantee the leader-following consensus while excluding the Zeno behavior. Furthermore, for the first time, an algorithm to actively adjust the leader adjacency matrix is presented, which efficiently expands the application range of some existing criteria. An example is finally given to illustrate the effectiveness of theoretical results.

Coordination for Linear Multiagent Systems With Dynamic Interaction Topology in the Leader-Following Framework

Abstract: This paper considers mainly the leader-following consensus for multiple agents with general linear system dynamics under switching topologies. Three different settings are systematically considered. We first consider the setting that the underlying interaction topologies switch arbitrarily among the possible weakly connected digraphs and then extend it to a more general setting that the weak connectivity of the interaction topologies is kept for some disconnected time intervals with short length due to the communication constraints among agents. Exponentially, consensus control is proved to be achieved, and the convergence rate can be specified as well for both settings in spite of the relaxed conditions on the system dynamics of each individual agent which even allow that each agent has exponentially unstable mode, while for the last case where the weak connectivity is only maintained on the joint of the interaction topologies, consensus control is proved to be achieved when the system matrix of each individual agent satisfies certain stability conditions.

Interacting Multiagent Systems: Kinetic equations and Monte Carlo methods

Abstract: The description of emerging collective phenomena and self-organization in systems composed of large numbers of individuals has gained increasing interest from various research communities in biology, ecology, robotics and control theory, as well as sociology and economics. Applied mathematics is concerned with the construction, analysis and interpretation of mathematical models that can shed light on significant problems of the natural sciences as well as our daily lives. To this set of problems belongs the description of the collective behaviours of complex systems composed by a large enough number of individuals. Examples of such systems are interacting agents in a financial market, potential voters during political elections, or groups of animals with a tendency to flock or herd. Among other possible approaches, this book provides a step-by-step introduction to the mathematical modelling based on a mesoscopic description and the construction of efficient simulation algorithms by Monte Carlo methods. The arguments of the book cover various applications, from the analysis of wealth distributions, the formation of opinions and choices, the price dynamics in a financial market, to the description of cell mutations and the swarming of birds and fishes. By means of methods inspired by the kinetic theory of rarefied gases, a robust approach to mathematical modelling and numerical simulation of multi-agent systems is presented in detail. The content is a useful reference text for applied mathematicians, physicists, biologists and economists who want to learn about modelling and approximation of such challenging phenomena.