Multi‐agent system for knowledge‐based event recognition and composition

This work presents a multi‐agent system for knowledge‐based high‐level event composition, which interprets activities, behaviour and situations semantically in a scenario with multi‐sensory monitoring. A perception agent (plurisensory agent and visual agent)‐based structure is presented. The agents process the sensor information and identify (agent decision system) significant changes in the monitored signals, which they send as simple events to the composition agent that searches for and identifies pre‐defined patterns as higher‐level semantic composed events. The structure has a methodology and a set of tools that facilitate its development and application to different fields without having to start from scratch. This creates an environment to develop knowledge‐based systems generally for event composition. The application task of our work is surveillance, and event composition/inference examples are shown which characterize an alarming situation in the scene and resolve identification and tracking problems of people in the scenario being monitored.     

Corruptible social agents

Agent‐based virtual simulations of social systems susceptible to corruption (e.g., police agencies) require agents capable of exhibiting corruptible behaviors to achieve realistic simulations and enable the analysis of corruption as a social problem. This paper proposes a formal belief‐desire‐intention framework supported by the functional event calculus and fuzzy logic for modeling corruption based on the integrity level of social agents and the influence of corrupters on them. Corruptible social agents are endowed with beliefs, desires, intentions, and corrupt‐prone plans to achieve their desires. This paper also proposes a fuzzy logic system to define the level of impact of corruption‐related events on the degree of belief in the truth of anti‐corruption factors (e.g., the integrity of the leader of an organization). Moreover, an agent‐based model of corruption supported by the proposed belief‐desire‐intention framework and the fuzzy logic system was devised and implemented. Results obtained from agent‐based simulations are consistent with actual macro‐level patterns of corruption reported in the literature. The simulation results show that (i) the bribery rate increases as more external entities attempt to bribe agents and (ii) the more anti‐corruption factors agents believe to be true, the less prone to perpetrate acts of corruption. Copyright © 2014 John Wiley & Sons, Ltd.     

Event‐Based Consensus Controller for Linear Multi‐Agent Systems Over Directed Communication Topologies: A Co‐Design Approach

The paper addresses the distributed event‐triggered consensus problem in directed topologies for multi‐agent systems (MAS) with general linear dynamic agents. A co‐design approach is proposed to determine parameters of the consensus controller and its event‐triggered mechanism (ETM), simultaneously. This approach guarantees asymptotic stability along with decreasing data transmission among agents. In the proposed event‐based consensus controller, each agent broadcasts data to the neighbors only at its own triggering instants; this differs from previous studies in which continuous data streams among agents were required. Furthermore, the proposed control law is based on the piecewise constant functions of the measurement values, which are updated at triggering instants. In this case the control scheme decreases the communication network usage, energy consumption, and wear of the actuator. As a result, it facilitates distributed implementation of the proposed consensus controller for real‐world applications. A theorem is proved to outline sufficient conditions to guarantee the asymptotic stability of the closed‐loop system with the event‐based consensus controller. Another theorem is also proved to show the Zeno behavior exclusion. As a case study, the proposed event‐based controller is applied for a diving consensus problem to illustrate the effectiveness of the method.     

Consensus of multi‐agent systems with time‐varying topology: An event‐based dynamic feedback scheme

The event‐based control strategy is an effective methodology for reducing the controller update and communication over the network. In this paper, the event‐based consensus of multi‐agent systems with linear dynamics and time‐varying topology is studied. For each agent, a state‐dependent threshold with an exponentially decaying bound is presented to determine the event times, and a new event‐based dynamic feedback scheme is proposed. It is shown that the controller update for each agent is only dependent on its own event times, which reduces significantly the controller update or computation for each agent. Moreover, based on the event‐based dynamic feedback scheme and the event triggering function presented in this paper, the continuous communication among neighboring agents is avoided, and the Zeno‐behavior of the closed‐loop systems is excluded. A numerical example is given to illustrate the effectiveness of theoretical results. Copyright © 2016 John Wiley & Sons, Ltd.     

NNs‐Based Event‐Triggered Consensus Control of a Class of Uncertain Nonlinear Multi‐Agent Systems

We are concerned with the consensus problem for a class of uncertain nonlinear multi‐agent systems (MASs) connected through an undirected communication topology via event‐triggered approaches in this paper. Two distributed control strategies, the adaptive centralized event‐triggered control one and adaptive distributed event‐triggered control one, are presented utilizing neural networks (NNs) and event‐driven mechanisms, where the advantages of the proposed control laws lie that they remove the requirement for exact priori knowledge about parameters of individual agents by taking advantage of NNs approximators and they save computing and communication resources since control tasks only execute at certain instants with respect to predefined threshold functions. Also, the trigger coefficient can be regulated adaptively with dependence on state errors to ensure not only the control performance but also the efficiency of the network interactions. It is proven that all signals in the closed‐loop system are bounded and the Zeno behavior is excluded. Finally, simulation examples are presented for illustration of the theoretical claims.     

Event‐Based Semiglobal Consensus of Homogenous Linear Multi‐Agent Systems Subject to Input Saturation

In this paper, we consider the semiglobal leader‐following consensus of general linear multi‐agent systems subject to input saturation. First, an event‐triggered control protocol is provided to ensure semiglobal consensus of the multi‐agent systems, in which the agents should continuously monitor the information of their neighbors. Second, a self‐triggered control protocol is proposed to guarantee the semiglobal consensus of the multi‐agent systems, in which the agents only have access to the information of their neighbors in discrete time instants. Moreover, both event‐triggered control protocol and self‐triggered control protocol are proved to be Zeno‐free, that is, the inter‐event times for such two protocols have positive lower bounds. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed event‐based semiglobal consensus protocols.     

Event‐based asynchronous communication and sampled control for synchronization of multiagent networks with input saturation

This paper investigates the problem of event‐based synchronization of linear dynamical networks subject to input saturation. The asynchronous neighboring information transmission is triggered by distributed events. The sampled control technique is utilized to exclude both the internal Zeno behavior of each agent and the network Zeno behavior attributed to neighboring agents. Allowing the input saturation to be attained, an event‐based global synchronization algorithm is proposed for multiagent networks with neutrally stable dynamics. For general linear networks, an event‐triggered control protocol is designed using the modified algebraic Riccati equation, with a low‐gain cooperative control law proposed to achieve semiglobal synchronization. A numerical example is presented to illustrate the theoretical results.     

Distributed Adaptive Event‐Triggered Control for Leader‐Following Consensus of Multi‐Agent Systems

This paper studies the leader‐following consensus problem for Lipschitz nonlinear multi‐agent systems using novel event‐triggered controllers. A distributed adaptive law is introduced for the event‐based control strategy design such that the proposed controllers are independent of system parameters and only use the relative states of neighboring agents, and hence are fully distributed. Due to the introduction of an event‐triggered control scheme, the controller of the agent is only triggered at it's own event times, and thus reduces the amount of communication between controller and actuator and lowers the frequency of controller updates in practice. Based on a quadratic Lyapunov function, the event condition which uses only neighbor information and local computation at trigger instants is established. Infinite triggers within a finite time are also verified to be impossible. The effectiveness of the theoretical results are illustrated through simulation examples.     

Event‐triggered output synchronization of heterogeneous multi‐agent systems

This paper proposes a control architecture that employs event‐triggered control techniques to achieve output synchronization of a group of heterogeneous linear time‐invariant agents. We associate with each agent an event‐triggered output regulation controller and an event‐triggered reference generator. The event‐triggered output regulation controller is designed such that the regulated output of the agent approximately tracks a reference signal provided by the reference generator in the presence of unknown disturbances. The event‐triggered reference generator is responsible for synchronizing its internal state across all agents by exchanging information through a communication network linking the agents. We first address the output regulation problem for a single agent where we analyze two event‐triggered scenarios. In the first one, the output and input event detectors operate synchronously, meaning that resets are made at the same time instants, while in the second one, they operate asynchronously and independently of each other. It is shown that the tracking error is globally bounded for all bounded reference trajectories and all bounded disturbances. We then merge the results on event‐triggered output regulation with previous results on event‐triggered communication protocols for synchronization of the reference generators to demonstrate that the regulated output of each agent converges to and remains in a neighborhood of the desired reference trajectory and that the closed‐loop system does not exhibit Zeno solutions. Several examples are provided to illustrate the advantages and issues of every component of the proposed control architecture. Copyright © 2016 John Wiley & Sons, Ltd.     

Tracking Control for Stochastic Multi‐Agent Systems Based on Hybrid Event‐Triggered Mechanism

This paper deals with the leader‐following consensus for nonlinear stochastic multi‐agent systems. To save communication resources, a new centralized/distributed hybrid event‐triggered mechanism (HETM) is proposed for nonlinear multi‐agent systems. HETMs can be regarded as a synthesis of continuous event‐triggered mechanism and time‐driven mechanism, which can effectively avoid Zeno behavior. To model the multi‐agent systems under centralized HETM, the switched system method is applied. By utilizing the property of communication topology, low‐dimensional consensus conditions are obtained. For the distributed hybrid event‐triggered mechanism, due to the asynchronous event‐triggered instants, the time‐varying system method is applied. Meanwhile, the effect of network‐induced time‐delay on the consensus is also considered. To further reduce the computational resources by constantly testing whether the broadcast condition has been violated, self‐triggered implementations of the proposed event‐triggered communication protocols are also derived. A numerical example is given to show the effectiveness of the proposed method.     

Distributed output regulation of leader–follower multi‐agent systems

In this paper, distributed leader–follower control algorithms are presented for linear multi‐agent systems based on output regulation theory and internal model principle. By treating a leader to be followed as an exosystem, the proposed framework can be used to generalize existing multi‐agent coordination solutions to allow the identical agents to track an active leader with different dynamics and unmeasurable variables. Moreover, the obtained results for multi‐agent coordination control are an extension of previous work on centralized and decentralized output regulation to a distributed control context. Necessary and sufficient conditions for the distributed output regulation problem are given. Finally, distributed output regulation of some classes of multi‐agent systems with switching interconnection topologies are discussed via both static and dynamic feedback. Copyright © 2011 John Wiley & Sons, Ltd.     

An optimal effective controller for discrete event systems

An approach to the online synthesis of an optimal effective controller for discrete event systems is presented. The optimal effective controller can achieve the prescribed (cumulative) effectiveness measure while minimizing the total cost incurred for the execution of events. This approach is constructed over a generalized control framework for automata‐based discrete event systems, which allows event enforcement in addition to the (original) event disablement/enablement as the control mechanism. The optimal effective control policy generated by this approach is proved to be the least restrictive among all the possible optimal effective control policies for the given online expansion tree of the system behavior. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Event‐triggered distributed constrained consensus

We consider a distributed consensus problem for continuous‐time multi‐agent systems with set constraints on the final states. To save communication costs, an event‐triggered communication‐based protocol is proposed. By comparing its own instantaneous state with the one previously broadcasted to neighbours, each agent determines the next communication time. Based on this event‐triggered communication, each agent is not required to continuously monitor its neighbours' state and the communication only happens at discrete time instants. We show that, under some mild conditions, the constrained consensus of the multi‐agent system with the proposed protocol can be achieved with an exponential convergence rate. A lower bound of the transmission time intervals is provided that can be adjusted by choosing different values of parameters. Numerical examples illustrate the results. Copyright © 2016 John Wiley & Sons, Ltd.     

Mechanisms for object caching in distributed applications using Java RMI

Remote Method Invocation (RMI), a mechanism to access remote objects in Java‐based distributed applications, uses network communication for each method invocation. Consequently, using RMI in a wide‐area environment can cause poor application performance. One solution to improve performance is to cache the objects such that network communication is not necessary for each method invocation. In this paper, we present mechanisms to transparently add object caching to RMI. These mechanisms are compatible with existing RMI applications and use an event‐based model to support different consistency policies. The mechanisms also include the ability to adaptively select the consistency policy for an object based on its usage pattern. A novel feature of our mechanisms is the use of a ‘reduced object’, which is a partial representation of the RMI object. We experimentally evaluate and demonstrate the benefits of our mechanisms. Copyright © 2006 John Wiley & Sons, Ltd.     

Exploring Trading Strategies and Their Effects in the Foreign Exchange Market

One of the most critical issues that developers face in developing automatic systems for electronic markets is that of endowing the agents with appropriate trading strategies. In this article, we examine the problem in the foreign exchange (FX) market, and we use an agent‐based market simulation to examine which trading strategies lead to market states in which the stylized facts (statistical properties) of the simulation match those of the FX market transactions data. Our goal is to explore the emergence of the stylized facts, when the simulated market is populated with agents using different strategies: a variation of the zero intelligence with a constraint strategy, the zero‐intelligence directional‐change event strategy, and a genetic programming‐based strategy. A series of experiments were conducted, and the results were compared with those of a high‐frequency FX transaction data set. Our results show that the zero‐intelligence directional‐change event agents best reproduce and explain the properties observed in the FX market transactions data. Our study suggests that the observed stylized facts could be the result of introducing a threshold that triggers the agents to respond to periodic patterns in the price time series. The results can be used to develop decision support systems for the FX market.     

Active optimistic and distributed message logging for message‐passing applications

Message logging is an attractive solution to provide fault tolerance for message‐passing applications because it is more scalable than coordinated checkpointing. Sender‐based message logging is a well‐known optimization that allows the saving of message payload in the sender memory. Thus, only message reception events have to be logged reliably by using an event logger. This paper proposes solutions to further improve message logging protocol scalability. In existing works on message logging, the event logger has always been considered as a centralized process. We propose a distributed event logger that takes advantage of multi‐core processors that are to be executed in parallel with application processes, leveraging the volatile memory of the nodes to save events reliably. We also propose the combination of our distributed event logger and O2P, an active optimistic message logging protocol using a gossip‐based protocol to disseminate information on new stable events. Our distributed event logger and O2P are implemented in the Open MPI library. Our results show the following: (i) distributed event logging improves message logging protocol scalability and (ii) using O2P with a distributed event logger provides an efficient and scalable fault‐tolerant solution for message‐passing applications. Copyright © 2011 John Wiley & Sons, Ltd.     

Robust and nonfragile consensus of positive multiagent systems via observer‐based output‐feedback protocols

This article investigates the consensus problem for positive multiagent systems via an observer‐based dynamic output‐feedback protocol. The dynamics of the agents are modeled by linear positive systems and the communication topology of the agents is expressed by an undirected connected graph. For the consensus problem, the nominal case is studied under the semidefinite programming framework while the robust and nonfragile cases are investigated under the linear programming framework. It is required that the distributed state‐feedback controller and observer gains should be structured to preserve the positivity of multiagent systems. Necessary and/or sufficient conditions for the analysis of consensus are obtained by using positive systems theory and graph theory. For the nominal case, necessary and sufficient conditions for the codesign of state‐feedback controller and observer of consensus are derived in terms of matrix inequalities. Sufficient conditions for the robust and nonfragile consensus designs are derived and the codesign of state‐feedback controller and observer can be obtained in terms of solving a set of linear programs. Numerical simulations are provided to show the effectiveness and applicability of the theoretical results and algorithms.     

A GENERIC TRUST FRAMEWORK FOR LARGE‐SCALE OPEN SYSTEMS USING MACHINE LEARNING

In many large‐scale distributed systems and on the Web, agents need to interact with other unknown agents to carry out some tasks or transactions. The ability to reason about and assess the potential risks in carrying out such transactions is essential for providing a safe and reliable interaction environment. A traditional approach to reason about the risk of a transaction is to determine if the involved agent is trustworthy on the basis of its behavior history. As a departure from such traditional trust models, we propose a generic, trust framework based on machine learning where an agent uses its own previous transactions (with other agents) to build a personal knowledge base. This is used to assess the trustworthiness of a transaction on the basis of the associated features, particularly using the features that help discern successful transactions from unsuccessful ones. These features are handled by applying appropriate machine learning algorithms to extract the relationships between the potential transaction and the previous ones. Experiments based on real data sets show that our approach is more accurate than other trust mechanisms, especially when the information about past behavior of the specific agent is rare, incomplete, or inaccurate.     

Distributed Consensus of Multi‐Agent Networks Via Event‐Triggered Pinning Control

This paper is concerned with distributed consensus between two multi‐agent networks with the same topology structure. Considering one network as the leaders' network and the other one as the followers' network, a new event‐triggered pinning control scheme is proposed to realize distributed consensus between these two networks. By utilizing the graph theory and Lyapunov functional method, consensus criteria are derived in the form of linear matrix inequalities. Moreover, distributed consensus of multi‐agent networks with Lipschitz nonlinear dynamics is also discussed. Numerical simulations are provided to demonstrate the effectiveness of the theoretical analysis.