Abstract: In this study, the consensus problem of heterogeneous multi-agent system is considered. First, the heterogeneous multi-agent system is proposed which is composed of first-order and second-order integrator agents in two aspects. Then, the consensus problem of heterogeneous multi-agent system is discussed with the linear consensus protocol and the saturated consensus protocol, respectively. By applying the graph theory and Lyapunov direct method, some sufficient conditions for consensus are established when the communication topologies are undirected connected graphs and leader-following networks. Finally, some examples are presented to illustrate the theoretical results.

Abstract: Agent-based computing is a diverse research domain concerned with the building of intelligent software based on the concept of "agents". In this paper, we use Scientometric analysis to analyze all sub-domains of agent-based computing. Our data consists of 1,064 journal articles indexed in the ISI web of knowledge published during a 20 year period: 1990---2010. These were retrieved using a topic search with various keywords commonly used in sub-domains of agent-based computing. In our proposed approach, we have employed a combination of two applications for analysis, namely Network Workbench and CiteSpace--wherein Network Workbench allowed for the analysis of complex network aspects of the domain, detailed visualization-based analysis of the bibliographic data was performed using CiteSpace. Our results include the identification of the largest cluster based on keywords, the timeline of publication of index terms, the core journals and key subject categories. We also identify the core authors, top countries of origin of the manuscripts along with core research institutes. Finally, our results have interestingly revealed the strong presence of agent-based computing in a number of non-computing related scientific domains including Life Sciences, Ecological Sciences and Social Sciences.

Abstract: In this paper, we investigate the use of event models for automated planning. Event models are the action defining structures used to define a semantics for dynamic epistemic logic. Using event models, two issues in planning can be addressed: Partial observability of the environment and knowledge. In planning, partial observability gives rise to an uncertainty about the world. For single-agent domains, this uncertainty can come from incomplete knowledge of the starting situation and from the nondeterminism of actions. In multi-agent domains, an additional uncertainty arises from the fact that other agents can act in the world, causing changes that are not instigated by the agent itself. For an agent to successfully construct and execute plans in an uncertain environment, the most widely used formalism in the literature on automated planning is “belief states”: sets of different alternatives for the current state of the world. Epistemic logic is a significantly more expressive and theoretically better foun...

Abstract: Agent-based simulation (ABS) is an approach to modeling systems comprised of individual, autonomous, interacting “agents.” Agent-based modeling offers ways to more easily model individual behaviors and how behaviors affect others in ways that have not been available before. There is much interest in developing agent-based models for many application problem domains. Applications range from modeling agent behavior in supply chains and the stock market, to predicting the success of marketing campaigns and the spread of epidemics, to projecting the future needs of the healthcare system. Progress in the area suggests that ABS promises to have far-reaching effects on the way that businesses use computers to support decision-making and researchers use agent-based models as electronic laboratories to aid in discovery. This brief tutorial introduces agent-based modeling and simulation by describing the basic ideas of ABS, discussing some applications, and addressing methods for developing agent-based models.

Abstract: This study concerns the consensus of a network of agents with general linear or linearised dynamics, whose communication topology contains a directed spanning tree. An observer-type consensus protocol based on the relative outputs of the neighbouring agents is adopted. The notion of consensus region is introduced, as a measure for the robustness of the protocol and as a basis for the protocol design. For neutrally stable agents, it is shown that there exists a protocol achieving consensus together with a consensus region that is the entire open right-half plane if and only if each agent is stabilisable and detectable. An algorithm is further presented for constructing such a protocol. For consensus with a prescribed convergence speed, a multi-step protocol design procedure is given, which yields an unbounded consensus region and at the same time maintains a favourable decoupling property. Finally, the consensus algorithms are extended to solve the formation control problems.

Abstract: The recent adoption of ubiquitous computing technologies has enabled capturing large amounts of human behavioral data The digital footprints computed from these datasets provide information for the study of social and human dynamics, including social networks and mobility patterns, key elements for the effective modeling of virus spreading Traditional epidemiologic models do not consider individual information and hence have limited ability to capture the inherent complexity of the disease spreading process To overcome this limitation, agent-based models have recently been proposed as an effective approach to model virus spreading However, most agent-based approaches to date have not included real-life data to characterize the agents' behavior In this paper we propose an agent-based system that uses social interactions and individual mobility patterns extracted from call detail records to accurately model virus spreading The proposed approach is applied to study the 2009 H1N1 outbreak in Mexico and to evaluate the impact that government mandates had on the spreading of the virus Our simulations indicate that the restricted mobility due the government mandates reduced by 10% the peak number of individuals infected by the virus and postponed the peak of the pandemic by two days

Abstract: A class of networked multi-agent systems is studied in this study where each agent has an identical dynamics of a simple integrator and the topology of the connections is fixed. It is proved that, when there are saturation constraints, a general consensus protocol widely used in the literatures for this class of multi-agent systems remains valid. As an extension, a 'bang-bang' type of consensus protocol is proposed to achieve the finite-time consensus, which relaxes the previous undirected connection assumption.

Abstract: This paper provides a comprehensive overview of long-term R&D activities of the Rockwell Automation (RA) company in the field of holonic and agent-based manufacturing control systems. It presents a coherent framework of methodologies for designing agent-based control systems, tools that support implementation and validation of them, and agent applications that were developed for various industrial systems. The common attribute is the integration of novel techniques, such as multiagent systems or semantics with the current “old-fashioned” automation architectures represented mainly by programmable logic controllers. Retaining the ability of the control system to meet the strict real-time constraints and concurrently raise its intelligence has always been of highest importance. The paper does not focus merely on RA's work, but discusses all its aspects in a context of other existing works in this area.

Abstract: Tutorial Dialog Systems that employ Conversational Agents (CAs) to deliver instructional content to learners in one-on-one tutoring settings have been shown to be effective in multiple learning domains by multiple research groups. Our work focuses on extending this successful learning technology to collaborative learning settings involving two or more learners interacting with one or more agents. Experience from extending existing techniques for developing conversational agents into multiple-learner settings highlights two underlying assumptions from the one-learner setting that do not generalize well to the multiuser setting, and thus cause difficulties. These assumptions include what we refer to as the near-even participation assumption and the known addressee assumption. A new software architecture called Basilica that allows us to address and overcome these limitations is a major contribution of this article. The Basilica architecture adopts an object-oriented approach to represent agents as a network composed of what we refer to as behavioral components because they enable the agents to engage in rich conversational behaviors. Additionally, we describe three specific conversational agents built using Basilica in order to illustrate the desirable properties of this new architecture.

Abstract: We use a high-gain methodology to construct linear decentralized controllers for consensus, in networks with identical but general multi-input linear time-invariant (LTI) agents and quitegeneral time-invariant and time-varying observation topologies.

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Abstract: We introduce an approach for stable deployment of agents onto families of planar curves, namely, 1-D formations in 2-D space. The agents' collective dynamics are modeled by the reaction-advection-diffusion class of partial differential equations (PDEs), which is a broader class than the standard heat equation and generates a rich geometric family of deployment curves. The PDE models, whose state is the position of the agents, incorporate the agents' feedback laws, which are designed based on a spatial internal model principle. Namely, the agents' feedback laws allow the agents to deploy to a family of geometric curves that correspond to the model's equilibrium curves, parameterized by the continuous agent identity α ∈ [0,1] . However, many of these curves are open-loop unstable. Stable deployment is ensured by leader feedback, designed in a manner similar to the boundary control of PDEs. By discretizing the PDE model with respect to α , we impose a fixed communication topology, specifically a chain graph, on the agents and obtain control laws that require communication with only an agent's nearest neighbors on the graph. A PDE-based approach is also used to design observers to estimate the positions of all the agents, which are needed in the leader's feedback, by measuring only the position of the leader's nearest neighbor. Hence, the leader uses only local information when employing output feedback.

Abstract: Recent years have seen an increase in the application of ideas from the social sciences to computational systems. Nowhere has this been more pronounced than in the domain of multiagent systems. Because multiagent systems are composed of multiple individual agents interacting with each other many parallels can be drawn to human and animal societies. One of the main challenges currently faced in multiagent systems research is that of social control. In particular, how can open multiagent systems be configured and organized given their constantly changing structure? One leading solution is to employ the use of social norms. In human societies, social norms are essential to regulation, coordination, and cooperation. The current trend of thinking is that these same principles can be applied to agent societies, of which multiagent systems are one type. In this article, we provide an introduction to and present a holistic viewpoint of the state of normative computing (computational solutions that employ ideas based on social norms.) To accomplish this, we (1) introduce social norms and their application to agent-based systems; (2) identify and describe a normative process abstracted from the existing research; and (3) discuss future directions for research in normative multiagent computing. The intent of this paper is to introduce new researchers to the ideas that underlie normative computing and survey the existing state of the art, as well as provide direction for future research.

Abstract: The agents and multiagent systems technology is actively researched by the academia and industrial community. However, the technology is particularly popular in the manufacturing domain, while the applications in other domains of industrial control are scarce. This survey focuses exclusively on the technology applications in the automation of continuous industrial processes, as the differences in the technology adoption between the process automation and manufacturing are significant. A large part of the literature on the subject is reviewed. The analysis of the literature is provided from several points of view, the main trends of research are described, including the shift of the researchers' interest from the agent-based supervisory control to the low-level agent-based control algorithms. Conclusions are provided regarding the lack of the technology support on the part of control instrumentation vendors; probable directions of the development are indicated, which turn out to be especially promising in the domain of biotechnological processes.

Abstract: This paper studies a flexible job shop problem considering dynamic events such as stochastic job arrivals, uncertain processing times, and unexpected machine breakdowns. Also, the considered job shop problem has routing flexibility and process flexibility. A multi-agent scheduling system has been developed for solution with good quality and robustness. A pheromone-based approach is proposed for coordination among agents. The proposed multi-agent approach is compared with five dispatching rules from literature via simulation experiments to statistical analysis. The simulation experiments are performed under various experimental settings such as shop utilization level, due date tightness, breakdown level, and mean time to repair. The results show that the proposed agent-based approach performs well under all problem settings.

Abstract: In this paper we aim to implement a highly distributed information infrastructure-MADIP by using Intelligent Agent paradigm, which is able to notify the responsible care-provider of abnormality automatically, offer distance medical advice, and perform continuous health monitoring for those who need it. To confront the issues of interoperability, scalability, and openness in heterogeneous e-health environments, a FIPA2000 standard compliant agent development platform-JADE (Java Agent DEvelopment Framework) was adopted for the design and implementation of the proposed intelligent multi-agent based MADIP system.

Abstract: Robust static output-feedback controllers are designed that achieve consensus in networks of heterogeneous agents modeled as nonlinear systems of relative degree two. Both ideal communication networks and networks with communication constraints are considered, e.g., with limited communication range or heterogeneous communication delays. All design conditions that are presented are scalable to large and heterogeneous networks because the controller parameters depend only on the dynamics of the corresponding agent and its neighbors, but not on other agents in the network.

Abstract: A widely applied strategy for workload sharing is to equalize the workload assigned to each resource. In mobile multiagent systems, this principle directly leads to equitable partitioning policies whereby: 1) the environment is equitably divided into subregions of equal measure; 2) one agent is assigned to each subregion; and 3) each agent is responsible for service requests originating within its own subregion. The current lack of distributed algorithms for the computation of equitable partitions limits the applicability of equitable partitioning policies to limited-size multiagent systems operating in known, static environments. In this paper, first we design provably correct and spatially distributed algorithms that allow a team of agents to compute a convex and equitable partition of a convex environment. Second, we discuss how these algorithms can be extended so that a team of agents can compute, in a spatially distributed fashion, convex and equitable partitions with additional features, e.g., equitable and median Voronoi diagrams. Finally, we discuss two application domains for our algorithms, namely dynamic vehicle routing for mobile robotic networks and wireless ad hoc networks. Through these examples, we show how one can couple the algorithms presented in this paper with equitable partitioning policies to make these amenable to distributed implementation. More in general, we illustrate a systematic approach to devise spatially distributed control policies for a large variety of multiagent coordination problems. Our approach is related to the classic Lloyd algorithm and exploits the unique features of power diagrams.

Abstract: Self-organisation, self-regulation, self-repair and self-maintenance are promising conceptual approaches for dealing with complex distributed interactive software and information-handling systems. Self-organising applications dynamically change their functionality and structure without direct user intervention, responding to changes in requirements and the environment. This is the first book to offer an integrated view of self-organisation technologies applied to distributed systems, particularly focusing on multiagent systems. The editors developed this integrated book with three aims: to explain self-organisation concepts and principles, using clear definitions and a strong theoretical background; to examine how self-organising behaviour can be modelled, analysed and systematically engineered into agent behaviour; and to assess the types of problems that can be solved using self-organising multiagent systems. The book comprises chapters covering all three dimensions, synthesising up-to-date research work and the latest technologies and applications. The book offers dedicated chapters on concepts such as self-organisation, emergence in natural systems, software agents, stigmergy, gossip, cooperation and immune systems. The book then explains how to engineer artificial self-organising software, in particular it examines methodologies and middleware infrastructures. Finally, the book presents diverse applications of self-organising software, such as constraint satisfaction, trust management, image recognition and networking. The book will be of interest to researchers working on emergent phenomena and adaptive systems. It will also be suitable for use as a graduate textbook, with chapter summaries and exercises, and an accompanying website that includes teaching slides, exercise solutions and research project outlines. Self-organisation, self-regulation, self-repair and self-maintenance are promising conceptual approaches for dealing with complex distributed interactive software and information-handling systems. Self-organising applications dynamically change their functionality and structure without direct user intervention, responding to changes in requirements and the environment. This is the first book to offer an integrated view of self-organisation technologies applied to distributed systems, particularly focusing on multiagent systems. The editors developed this integrated book with three aims: to explain self-organisation concepts and principles, using clear definitions and a strong theoretical background; to examine how self-organising behaviour can be modelled, analysed and systematically engineered into agent behaviour; and to assess the types of problems that can be solved using self-organising multiagent systems. The book comprises chapters covering all three dimensions, synthesising up-to-date research work and the latest technologies and applications. The book offers dedicated chapters on concepts such as self-organisation, emergence in natural systems, software agents, stigmergy, gossip, cooperation and immune systems. The book then explains how to engineer artificial self-organising software, in particular it examines methodologies and middleware infrastructures. Finally, the book presents diverse applications of self-organising software, such as constraint satisfaction, trust management, image recognition and networking. The book will be of interest to researchers working on emergent phenomena and adaptive systems. It will also be suitable for use as a graduate textbook, with chapter summaries and exercises, and an accompanying website that includes teaching slides, exercise solutions and research project outlines.

Abstract: This paper investigates the joint effects of agent dynamic and network topology on the consensusability of linear discrete-time multi-agent systems via relative output feedback. An observer-based distributed control protocol is proposed. A necessary and sufficient condition for consensusability under this control protocol is given, which explicitly reveals how the intrinsic entropy rate of the agent dynamic and the eigenratio of the undirected communication graph affect consensusability. As a special case, multi-agent systems with discrete-time double integrator dynamics are discussed where a simple control protocol directly using two-step relative position feedback is provided to reach a consensus. Finally, the result is extended to solve the formation and formation-based tracking problems. The theoretical results are illustrated by simulations. Copyright © 2010 John Wiley & Sons, Ltd.

Abstract: A key component to future smart grids may be microgrid systems capable of integrating generation, load, and storage assets into an autonomous power system entity. As a potential building block for expanding power networks, microgrids can enable the broad integration of distributed energy resources (DER), as well as providing customers a means to optimize local assets based on multiple objectives. Pivotal to the implementation of microgrids are the power management and control architectures that will operate the microgrid systems. In this paper, a multi-agent based control architecture for microgrids, capable of coordinating and cooperatively achieving user-defined objectives is presented. Herein, unique agents that comprise a distributed multi-agent system (MAS) are developed according to Foundation for Intelligent Physical Agents (FIPA) guidelines. The authors present a method for facilitating the fundamental self-organizing and cooperative behavior amongst the microgrid agents. The MAS formulation developed is intended to lay the groundwork for a power management architecture that incorporates the integrated and robust operation of microgrid assets.