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.

A methodology for the analysis and design of multi-agent systems using JADE

Abstract: A methodology is proposed for the development of multi-agent systems using the JADE platform. The proposed methodology focuses on the key issues in the analysis and design of multi-agent systems. The analysis phase is generic in nature, while the design phase specifically focuses on the constructs provided by the popular FIPA-compliant JADE platform. The methodology essentially serves as a guide, providing a direction for the multi-agent system designer, while also giving them the opportunity to add or remove components as desired, based on the specific problem domain. In contrast to current methodologies, support is also provided for existing systems and people to be included and accounted for in the multi-agent system. The methodology is illustrated by applying it to a hypothetical but illustrative scenario. Moreover, it is presented in such a way that designers new to the field of agent-based computing and the JADE platform can quickly grasp the most important concepts in the development of a multi-agent system. Similarly, people currently familiar with the JADE platform can also benefit from the methodology, which, when applied, should lead to a significant reduction in system development time.

A Formal Model for Situated Multi-Agent Systems

Abstract: Contrary to cognitive approaches of agency where a lot of effort is devoted to the formalization of agent concepts, little work has been done on the formalization of situated multi-agent systems (situated MASs). In this paper we present a generic model for situated MASs. This model formally describes an abstract architecture for situated MASs. In this architecture each agent is situated in its local context that it is able to perceive and in which it can act. Since intelligence in situated MASs results from the interactions of agents with the environment rather than from their individual capabilities, the model takes an action-centric approach. The model deals with (1) the actions of agents in the environment, (2) ongoing activities in the environment, such as moving objects, and (3) the interactions between agents and ongoing activities through the environment. One model for situated MASs was described by J.Ferber and J.P. M¨ller. In this model all agents of the MAS act at one global pace, i.e.the agents are globally synchronized. Drawbacks of global synchronization are centralized control and poor scalability. We present a model that allows agents to synchronize locally. In this model there is no centralized entity that imposes all agents to act at one global pace, but instead agents themselves decide when they perform their next actions. The model supports simultaneous actions through regional synchronization. With regional synchronization agents form synchronized groups on the basis of their actual locality. Different groups can act asynchronously, while agents within one group act synchronously. The result is a model that does not suffer from the drawbacks of global synchronization while it preserves the properties for handling simultaneous actions. In the paper we apply the model to a simple MAS application. We show how the abstract model can be instantiated for a practical application. Then we follow a trace in the evolution of the application and demonstrate how the model deals with each particular step.

Intelligent Agents and Multi-Agent Systems

Abstract: The world’s industries are moving into the ‘new economy’ of electronic market. The success of this move depends on efficient and reliable management of the business processes that will drive the e-Market’s valuechain. Efficiency can only be achieved through automation. Reliability will be achieved by reliable and dependable process management systems. These electronic trans-corporate processes cover the range from basic business transactions, workflows to sophisticated business processes that rely on a high level of personalisation. Management of these processes requires safety critical computer systems that can survive local catastrophes. Multi-agent systems have this level of dependability and personalisation. An analysis of the full range of processes is followed by an implementation framework for their management using a powerful multiagent architecture.

Distributed event-triggered control of discrete-time heterogeneous multi-agent systems

Abstract: This paper investigates the consensus problem for a set of discrete-time heterogeneous multi-agent systems composed of two kinds of agents differed by their dynamics. The consensus control is designed based on the event-triggered communication scheme, which can lead to a significant reduction of the information communication burden in the multi-agent network. Meanwhile, only the communication between the agent and its local neighbors is needed, therefore, the designed control is essentially distributed. Based on the Lyapunov functional method and the Kronecker product technique, a sufficient condition is obtained to guarantee the consensus of heterogeneous multi-agent systems in terms of linear matrix inequality (LMI). Simulation results illustrate the effectiveness of the developed theory in the last.

Distributed Multi-Agent System-Based Load Frequency Control for Multi-Area Power System in Smart Grid

Abstract: This paper presents an intelligent controller for “load frequency control (LFC)” application in “smart grid (SG)”environment having changes in communication topology (CT) via a multi-agent system (MAS) technology. In this study, network-induced effects, time delay, and change in CT have been addressed to examine the system performance in a closed loop. An event-triggered control method is used to reduce the communication burden in a network. An intelligent controller based on reinforcement learning consists of two levels, estimator agent and controller agent, in each multi-area system. Particle swarm optimization is used to tune the controller parameters. Furthermore, the proposed control strategy and system architecture as MAS for LFC in SG are analyzed in detail, verified for various load conditions and different network configurations. In addition, mean-square error of the power system states with CT is also analyzed. The results of this study validate the feasibility of the proposed control, as well as the capability of the MAS for the operation of LFC in SG with changes in CT.