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.

Distributed MPC for formation of multi-agent systems with collision avoidance and obstacle avoidance

Abstract: The paper is concerned with the problem of distributed model predictive control (DMPC) for formation of multiple linear second-order agents with collision avoidance and obstacle avoidance. All the agents are permitted to implement optimization simultaneously at each time step. The assumed input trajectory and state trajectory are introduced to obtain a computationally tractable optimization problem in a distributed manner. As a result, a compatibility constraint is required to ensure the consistency between each agent׳s real operation and its plan and to establish the agreement among agents. The terminal ingredients are tailored by making use of the specific form of the system model and the control objective. The terminal set is ensured to be positively invariant with the designed terminal controller. The collision avoidance constraint and the obstacle avoidance constraint are satisfied for any state in the terminal set. The weighted matrix of the terminal cost is determined by solving a Lyapunov equation. Moreover, recursive feasibility of the resulting optimization problem is guaranteed and closed-loop stability of the whole system is ensured. Finally, a numerical example is given to illustrate the effectiveness of the proposed algorithm.

Using communication to reduce locality in distributed multiagent learning

Abstract: . This paper attempts to bridge the fields of machine learning, robotics, and distributed AI. It discusses the use of communication in reducing the undesirable effects of locality in fully distributed multi-agent systems with multiple agents robots learning in parallel while interacting with each other. Two key problems, hidden state and credit assignment, are addressed by applying local undirected broadcast communication in a dual role: as sensing and as reinforcement. The methodology is demonstrated on two multi-robot learning experiments. The first describes learning a tightly-coupled coordination task with two robots, the second a loosely-coupled task with four robots learning social rules. Communication is used to (1) share sensory data to overcome hidden state and (2) share reinforcement to overcome the credit assignment problem between the agents and bridge the gap between local individual and global group pay-off.

The Logical Modelling of Computational Multi-Agent Systems

Abstract: THE aim of this thesis is to investigate logical formalisms for describing, reasoning about, specifying, and perhaps ultimately verifying the properties of systems composed of multiple intelligent computational agents. There are two obvious resources available for this task. The first is the (largely AI) tradition of reasoning about the intentional notions (belief, desire, etc.). The second is the (mainstream computer science) tradition of temporal logics for reasoning about reactive systems. Unfortunately, neither resource is ideally suited to the task: most intentional logics have little to say on the subject of agent architecture, and tend to assume that agents are perfect reasoners, whereas models of concurrent systems from mainstream computer science typically deal with the execution of individual program instructions. This thesis proposes a solution which draws upon both resources. It defines a model of agents and multi-agent systems, and then defines two execution models, which describe how agents may act and interact. The execution models define what constitutes an acceptable run of a system. A run may then act as a model for a temporal logic; this logic can subsequently be used to describe and reason about multi-agent systems. A number of logics, with various properties, are developed in this way. Several detailed examples are presented, showing how the logics may be used for specifying and reasoning about multi-agent systems. The thesis includes a detailed literature survey.

Research directions for service-oriented multiagent systems

Abstract: Today's service-oriented systems realize many ideas from the research conducted a decade or so ago in multiagent systems. Because these two fields are so deeply connected, further advances in multiagent systems could feed into tomorrow's successful service-oriented computing approaches. This article describes a 15-year roadmap for service-oriented multiagent system research.

Asynchronous Distributed Optimization With Event-Driven Communication

Abstract: We consider problems where multiple agents cooperate to control their individual state so as to optimize a common objective while communicating with each other to exchange state information. Since communication costs can be significant, especially when the agents are wireless devices with limited energy, we seek conditions under which communication of state information among nodes can be restricted while still ensuring that the optimization process converges. We propose an asynchronous (event-driven) optimization scheme that limits communication to instants when some state estimation error function at a node exceeds a threshold and prove that, under certain conditions, such convergence is guaranteed when communication delays are negligible. We subsequently extend the analysis to include communication delays as long as they are bounded. We apply this approach to a sensor network coverage control problem where the objective is to maximize the probability of detecting events occurring in a given region and show that the proposed asynchronous approach may significantly reduce communication costs, hence also prolonging the system's lifetime, without any performance degradation.