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 collaborative driving system based on multiagent modelling and simulations

Abstract: Collaborative driving is a growing domain of intelligent transportation systems (ITS) that makes use of communications to autonomously guide cooperative vehicles on an automated highway system (AHS). In this paper, we address this issue by using a platoon of cars considered as more or less autonomous software agents. To achieve this, we propose a hierarchical driving agent architecture based on three layers (guidance layer, management layer and traffic control layer). This architecture has been used to develop centralized platoons, where the driving agent of the head vehicle coordinates other driving agents by applying strict rules, and decentralized platoons, where the platoon is considered as a group of driving agents with a similar degree of autonomy, trying to maintain a stable platoon. The latter decentralized model mainly considers an agent teamwork model based on a multiagent architecture, known as STEAM. The centralized and decentralized coordination models are finally compared using results from simulation scenarios that highlight safety, time efficiency and communication efficiency aspects for each model.

Land use decisions in developing countries and their representation in multi-agent systems

Abstract: Recent research on land use and land cover change (LUCC) has put more emphasis on the importance of understanding the decision-making of human actors, especially in developing countries. The quest is now for a new generation of LUCC models with a decision-making component. This paper deals with the question of how to realistically represent decision-making in land use models. Two main agent decision architectures are compared. Heuristic agents take sequential decisions following a pre-defined decision tree, while optimizing agents take simultaneous decisions by solving a mathematical programming model. Optimizing behaviour is often discarded as being unrealistic. Yet the paper shows that optimizing agents do have important advantages for empirical land use modelling and that multi-agent systems (MAS) offer an ideal framework for using the strengths of both agent decision architectures. The use of optimization models is advanced with a novel three-stage decision model of investment, production, and consump...

A market-based multi-agent system model for decentralized multi-project scheduling

Abstract: We consider a multi-project scheduling problem, where each project is composed of a set of activities, with precedence relations, requiring specific amounts of local and shared (among projects) resources. The aim is to complete all the project activities, satisfying precedence and resource constraints, and minimizing each project schedule length. The decision making process is supposed to be decentralized, with as many local decision makers as the projects. A multi-agent system model, and an iterative combinatorial auction mechanism for the agent coordination are proposed. We provide a dynamic programming formulation for the combinatorial auction problem, and heuristic algorithms for both the combinatorial auction and the bidding process. An experimental analysis on the whole multi-agent system model is discussed.

Towards a standardization of multi-agent system framework

Abstract: Fortunately, we are not the first to ask these questions, and researchers have already defined some helpful notions. First, authors have acknowledged that agents are entities within an environment, and that they can sense and act (not necessarily in that order). This means that agents are not isolated entities, and that they are able to communicate and collaborate with other entities. Simply put, agents that are not able to work together with other agents (humans included) are destined to become virtually useless.

Physical Safety and Cyber Security Analysis of Multi-Agent Systems: A Survey of Recent Advances

Abstract: Multi-agent systems (MASs) are typically composed of multiple smart entities with independent sensing, communication, computing, and decision-making capabilities. Nowadays, MASs have a wide range of applications in smart grids, smart manufacturing, sensor networks, and intelligent transportation systems. Control of the MASs are often coordinated through information interaction among agents, which is one of the most important factors affecting coordination and cooperation performance. However, unexpected physical faults and cyber attacks on a single agent may spread to other agents via information interaction very quickly, and thus could lead to severe degradation of the whole system performance and even destruction of MASs. This paper is concerned with the safety/security analysis and synthesis of MASs arising from physical faults and cyber attacks, and our goal is to present a comprehensive survey on recent results on fault estimation, detection, diagnosis and fault-tolerant control of MASs, and cyber attack detection and secure control of MASs subject to two typical cyber attacks. Finally, the paper concludes with some potential future research topics on the security issues of MASs.