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The purpose of this paper is to discuss the impacts of the communication time-delays to the distributed containment control of the second-order multi-agent systems with directed topology.

A basic theoretical analysis is first carried out for the containment control of the second-order multi-agent systems under directed topology without communication time-delay and a sufficient condition is proposed for the achievement of containment control. Based on the above result and frequency-domain analysis method, a sufficient condition is also derived for the achievement of containment control of the second-order multi-agent systems under directed topology with communication time-delays. Finally, simulation results are presented to support the effectiveness of the theoretical results.

For the achievement of containment control of the second-order multi-agent systems under directed topology with communication time-delay, the control gain in the control protocols is completely dependent on the communication topology structure and the maximum of time-delay in the control protocols is dependent on the given control gain and communication topology structure.

The paper investigates the containment control of the second-order multi-agent systems under directed topology with communication time-delays and presents a sufficient conditions for the achievement of containment control. The results and approach proposed in the paper may benefit interesting researchers.

This paper aims to study that for multi-agent systems, how to find proper control protocols to ensure synchronization when the input set of each agent is not the whole real axis but a discrete set, and how the coarseness of imprecise input sets affect the synchronization control of the multi-agent systems.

The paper uses a relative state feedback method and non-linear mapping functions to design a proper control protocol which matches the coarseness of the input set and ensures synchronization. For theoretical analysis, the paper uses an error analysis method and mathematic induction to prove the effectiveness of the designed control protocol. The paper also uses a numerical example to show the correctness of the theoretical results.

The paper provides a method for protocol design when the input set of each agent is imprecise. The paper establishes a bi-direction relationship which suffices for synchronization between the coarseness of the input set and the synchronization precision, and finds that this relationship describes how the coarseness of the input set affects the synchronization control of the multi-agent system.

This paper only studies the case with logarithmically distributed and uniformly distributed discrete input sets. The authors are encouraged to study the synchronization control of multi-agent systems under input sets with more general distributions.

The paper includes implications for coordination control of multi-agent networks when the actuator of each agent is with a limited capacity, which leads to the case of discrete input sets with limit precision.

This paper fulfils an identified need to study how the coarseness of the input set of each agent affects the synchronization control of the whole multi-agent system.

The purpose of this paper is to study the dynamical group consensus of heterogeneous multi-agent systems with fixed topologies.

The tool used in this paper to model the topologies of multi-agent systems is algebraic graph theory. The matrix theory and stability theory are applied to research the group consensus of heterogeneous multi-agent systems with fixed topologies. The Laplace transform and Routh criterion are utilized to analyze the convergence properties of heterogeneous multi-agent systems.

It is discovered that the dynamical group consensus for heterogeneous multi-agent systems with first-order and second-order agents can be achieved under the reasonable hypothesizes. The group consensus condition is only relied on the nonzero eigenvalues of the graph Laplacian matrix.

The novelty of this paper is to investigate the dynamical group consensus of heterogeneous multi-agent systems with first-order and second-order agents and fixed topologies and obtain a sufficient group consensus condition.

The purpose of this paper is to enhance trust in e-commerce multi-agent systems by presenting a model, called RUU, to select the most trustworthy provider agent based on learning from previous interactions and computing reliability, unreliability and uncertainty.

The methodology comprises analyzing the most representative existing trust models, while a new concept was proposed and measured as unreliability. To make decision about the agents, RUU integrated reliability, unreliability and uncertainty components and used the TOPSIS multi-criteria decision method to select the most trustworthy provider agent. To evaluate the RUU model, the experimentation was carried out in two stages. First, the average accuracy of the model was investigated by simulating RUU in a multi-agent environment. Second, the performance of the model was compared with other related trust models.

The experimental results revealed that RUU model outperforms current models in providing accurate credibility measurements and computing an accurate trust mechanism for agents, also presenting a decision-making process to choose the most trustworthy provider agent.

The model presented based on different mathematical computations that take time to be calculated, which is a big limitation of computational models.

RUU enables an agent to make effective and sound decisions in light of the uncertainty that exists in e-commerce multi-agent environments.

This paper is beneficial to enhance the fulfilment of purchasing between provider and requester agents. In fact, the proposed model can ensure critical transactions performed securely in e-commerce multi-agent environments.

The aim of this paper is to address the problem of fault detection (FD) of linear continuous‐time multi‐agent systems.

A mixed H_∞/H₋ formulation of the FD problem using semi‐decentralized filters is presented.

It is shown that through a decomposition approach the drawbacks of the existing distributed FD design methods in multi‐agent systems can be effectively tackled. An extended linear matrix inequality (LMI) characterization is used to reduce the conservativeness of the design solution by introducing additional matrices in order to eliminate the couplings of the Lyapunov matrices with the agent's matrices.

It is shown that by applying the proposed decomposition approach the FD problem of multi‐agent systems can be solved by analyzing the problem of a set of decoupled systems whose order and complexity are equal to that of a single agent. This procedure will be useful for both simplifying the computational cost of the solution as well as for developing a fault detection filter having a semi‐decentralized architecture.

Application of this methodology to a network of micro‐air vehicles (MAVs) illustrates the effectiveness and capabilities of the proposed design methodology.

The feasibility of the use of reliable and self‐healing network of unmanned systems, cooperative networks, and multi‐agent systems will be significantly enhanced and improved by the development of advanced fault detection and isolation (FDI) technologies.

A semi‐decentralized fault detection (FD) methodology is developed for linear multi‐agent networked systems to reduce the order and complexity of the observers at each agent. A mixed H_∞/H₋ formulation of the FD problem by using semi‐decentralized filters is presented. Using this approach each agent can not only detect its own faults but also is able to detect its nearest neighbor agents’ faults.

The purpose of this paper is to enhance trust in multi-agent systems by presenting a new computational model, named reputation-distribute-conflict (R-D-C), to select the most trustworthy provider agent based on computing reputation, disrepute, and conflict of each provider agent.

R-D-C propose based on three vital components for evaluating trustworthiness of providers as reputation, disrepute, and conflict, where disrepute is a component almost all trust models ignored. The R-D-C model presents a computational method for evaluating to select the most trustworthy provider agent. In order to evaluate the R-D-C model, the experimentation was carried out in two stages, by designing a simulated multi-agent environment. First, the accuracy of the R-D-C model in computing R-D-C was investigated. Second, the performance of the model was compared with other existing trust models. Moreover, comparison of the performance of the R-D-C model with other models demonstrates that the R-D-C model performs significantly better than the other models. Therefore, the R-D-C model is capable of evaluating the trustworthiness of agents more accurately and it can select the most trustworthy provider better than the other models.

The results show that the R-D-C model works well in different multi-agent environments, even when the number of untrustworthy providers is higher than that of the trustworthy ones.

The R-D-C model is useful for researchers to enhance the safety of online transactions in multi-agent environments, especially if the researchers explore more components; in fact the R-D-C model is capable of adding these new components and selects the most trustworthy provider agent.

The purpose of this paper is to study the moving consensus of multi‐agent dynamical systems with time delays and directed weighted networks.

The approach used in the study, the topologies of multi‐agent dynamical systems with directed weighted networks is graph theories. The frequency domain is applied to research the movement characteristics of multi‐agent systems with time delays. The generalized Nyquist criterion and curvature theorem are utilized to analyze the consensus algorithm with heterogeneous input delays and heterogeneous communication delays.

It was discovered that the consensus for the delayed multi‐agent systems with asymmetric coupling weights can be achieved with the hypothesis of directed weighted network composed of n agents with a globally reachable node. The convergence condition is a decentralized consensus condition which uses only local information of each agent.

The novelty associated with this work is to present a new approach to study the consensus of delayed multi‐agent dynamical systems with directed weighted networks. The consensus condition obtained in the paper is less conservative than the consensus condition given in references.

A real-time production scheduling method for semiconductor back-end manufacturing process becomes increasingly important in industry 4.0. Semiconductor back-end manufacturing process is always accompanied by order splitting and merging; besides, in each stage of the process, there are always multiple machine groups that have different production capabilities and capacities. This paper studies a multi-agent based scheduling architecture for the radio frequency identification (RFID)-enabled semiconductor back-end shopfloor, which integrates not only manufacturing resources but also human factors.

The architecture includes a task management (TM) agent, a staff instruction (SI) agent, a task scheduling (TS) agent, an information management center (IMC), machine group (MG) agent and a production monitoring (PM) agent. Then, based on the architecture, the authors developed a scheduling method consisting of capability & capacity planning and machine configuration modules in the TS agent.

The authors used greedy policy to assign each order to the appropriate machine groups based on the real-time utilization ration of each MG in the capability & capacity (C&C) planning module, and used a partial swarm optimization (PSO) algorithm to schedule each splitting job to the identified machine based on the C&C planning results. At last, we conducted a case study to demonstrate the proposed multi-agent based real-time production scheduling models and methods.

This paper proposes a multi-agent based real-time scheduling framework for semiconductor back-end industry. A C&C planning and a machine configuration algorithm are developed, respectively. The paper provides a feasible solution for semiconductor back-end manufacturing process to realize real-time scheduling.

Supply chain management represents a critical competency in today’s global business environment and has been the focus of considerable, but mixed, information systems research. The research described in this paper builds on work in multi‐agent systems to argue that intelligent agents offer excellent potential and capability for supply chain management, and contributes to discussion and theory pertaining to electronic markets and supply chain disintermediation. Argues that the knowledge associated with intermediation work represents a key mediating variable between disintermediating technology and supply chain efficacy and discusses how intelligent agent technology can be employed to both intermediate and disintermediate the supply chain, attaining the cost and cycle‐time benefits of disintermediation without the attendant loss of human knowledge and expertise. The paper outlines a number of implications for theory and practice in information systems, and it formalizes some important research questions through a contingency framework to help stimulate and guide future work along these lines.

With the rapid development of e-commerce, logistics demand is increasing day by day. The modern warehousing with a multi-agent system as the core comes into being. This paper aims to study the task allocation and path-planning (TAPP) problem as required by the multi-agent warehouse system.

The TAPP problem targets to minimize the makespan by allocating tasks to the agents and planning collision-free paths for the agents. This paper presents the Hierarchical Genetic Highways Algorithm (HGHA), a hierarchical algorithm combining optimization and multi-agent path-finding (MAPF). The top-level is the genetic algorithm (GA), allocating tasks to agents in an optimized way. The lower level is the so-called highways local repair (HLR) process, avoiding the collisions by local repairment if and only if conflicts arise.

Experiments demonstrate that HGHA performs faster and more efficient for the warehouse scenario than max multi-flow. This paper also applies HGHA to TAPP instances with a hundred agents and a thousand storage locations in a customized warehouse simulation platform with MultiBots.

This paper formulates the multi-agent warehousing distribution problem, TAPP. The HGHA based on hierarchical architecture solves the TAPP accurately and quickly. Verifying the HGHA by the large-scale multi-agent simulation platform MultiBots.