Self-organization and multiagent systems: II. Applications and the development technology

Major trends in the development of modern information technologies are to a large extend determined by important practical problems that arise in economics, ecology, safety of society and individuals, and in other fields. Even though these problems seem to be quite different and the requirements for their software implementation are also different, they have many common features, which imply the most stringent requirements for modern information technologies. These features were analyzed in the first part of the present paper. That analysis showed that the new requirements for the model and software implementation of such problems are best met by the multiagent self-organizing system model. In this paper, we consider examples of using this model in various applications and describe their architectures and software implementation; in particular, multiagent self-organization models as applied for flood forecasting and planning and operational enterprise management are described. New capabilities of multiagent self-organizing systems are demonstrated using a self-learning system for detecting intrusions into computer networks as an example. Here, the problem of self-configuration of an overlay network is actually solved. The capabilities of a multiagent self-organizing system in large-scale control in real time are demonstrated using adaptive traffic control in large cities. For the software implementation of multiagent self-organizing systems, special development tools that are different from the existing ones are needed because the conventional top-down development paradigm is inappropriate for self-organizing architectures. The cause is that the global behavior of a multiagent self-organizing system emerges due to local interactions; therefore, it cannot be predicted in advance. For that reason, the bottom-up development model is more appropriate for such systems. In this paper, we give a brief review of the models and approaches proposed for this purpose. One of the promising approaches based on the use of the so-called self-organization design patterns is described in more detail. Results of using the multiagent self-organization model are discussed and prospects of its practical application are estimated.     

Intelligent control systems. I. Quantum computing and self-organization algorithm

The role and methodology of application of quantum computing in problems of design of robust intelligent control systems under the conditions of contingency control situations are discussed. The quantum self-organization control algorithm, which contains the self-organization control algorithm for robust knowledge bases as the particular case, is developed. The satisfaction of the introduced thermodynamic criterion (in the form of the minimum of the generalized entropy in the established relation between such qualitative control characteristics as stability, controllability, and robustness) is the goal of application of the quantum self-organization control algorithm for knowledge bases used in the control loop. The essentially nonlinear and globally unstable control object is used as the example for application of the quantum self-organization control algorithm to the solution of the vector optimization problem based on the decomposition of knowledge bases.     

Opportunities for multiagent systems and multiagent reinforcement learning in traffic control

The increasing demand for mobility in our society poses various challenges to traffic engineering, computer science in general, and artificial intelligence and multiagent systems in particular. As it is often the case, it is not possible to provide additional capacity, so that a more efficient use of the available transportation infrastructure is necessary. This relates closely to multiagent systems as many problems in traffic management and control are inherently distributed. Also, many actors in a transportation system fit very well the concept of autonomous agents: the driver, the pedestrian, the traffic expert; in some cases, also the intersection and the traffic signal controller can be regarded as an autonomous agent. However, the “agentification” of a transportation system is associated with some challenging issues: the number of agents is high, typically agents are highly adaptive, they react to changes in the environment at individual level but cause an unpredictable collective pattern, and act in a highly coupled environment. Therefore, this domain poses many challenges for standard techniques from multiagent systems such as coordination and learning. This paper has two main objectives: (i) to present problems, methods, approaches and practices in traffic engineering (especially regarding traffic signal control); and (ii) to highlight open problems and challenges so that future research in multiagent systems can address them.     

Declarative representations of multiagent systems

This paper explores the specification and semantics of multiagent problem-solving systems, focusing on the representations that agents have of each other. It provides a declarative representation for such systems. Several procedural solutions to a well-known test-bed problem are considered, and the requirements they impose on different agents are identified. A study of these requirements yields a representational scheme based on temporal logic for specifying the acting, perceiving, communicating, and reasoning abilities of computational agents. A formal semantics is provided for this scheme. The resulting representation is highly declarative, and useful for describing systems of agents solving problems reactively     

Controllability of heterogeneous multiagent systems

The existing results on controllability of multiagent systems (MASs) are mostly based on homogeneous nodes. This paper focuses on controllability of heterogeneous MASs, where the agents are modeled as two types. One type is that the agents have the same high‐order dynamics, and the interconnection topologies of the information flow in different orders are supposed to be different; the other type is that the agents have generic linear dynamics, and the dynamics are supposed to be heterogeneous. For the first type, the necessary and sufficient condition for controllability of heterogeneous‐topology system is derived via combination of Laplacian matrices. For the second type, the contribution also has two parts. The first part supposes that the agents have the same dimensional states and proves that controllability of this kind of MASs is equivalent to the controllability of each node and the whole interconnection topology, while the last parameter of the state feedback vector must not be 0. The second part supposes that the agents may have different dimensional states. For this kind of systems, the concept of β‐controllability is proposed. The necessary and sufficient condition for β‐controllability of heterogeneous‐dynamic systems is also derived and it is also proved that the feedback gain vectors have the effect to improve controllability. Different illustrative examples are provided to demonstrate the effectiveness of the theoretical results in this paper.     

Visualization and debugging of distributed multiagent systems

Visualizing the behavior of systems with distributed data, control, and process is a notoriously difficult task. Each component in the distributed system has only a local view of the whole setup, and the onus is on the user to integrate, into a coherent whole, the large amounts of limited information they provide. In this article, we describe an architecture and an implemented system for visualizing and controlling distributed multiagent applications. The system comprises a suite of tools, with each tool providing a different perspective of the application being visualized . Each tool interrogates the components of the distributed application, collates the returned information, and presents this information to users in an appropriate manner. This in essence, shifts the burden ofinference from the user to the visualizer. Our visualizer has been evaluated on four distributed multiagent systems: a travel management application, a telecommunications network management application, a business process management demonstrator, and an electronic commerce application. Lastly, we briefly show how the suite of tools can be used together for debugging multiagent applications - a process we refer to as debugging via corroboration.     

TRAMMAS: A tracing model for multiagent systems

Agent's flexibility and autonomy, as well as their capacity to coordinate and cooperate, are some of the features which make multiagent systems useful to work in dynamic and distributed environments. These key features are directly related to the way in which agents communicate and perceive each other, as well as their environment and surrounding conditions. Traditionally, this has been accomplished by means of message exchange or by using blackboard systems. These traditional methods have the advantages of being easy to implement and well supported by multiagent platforms; however, their main disadvantage is that the amount of social knowledge in the system directly depends on every agent actively informing of what it is doing, thinking, perceiving, etc. There are domains, for example those where social knowledge depends on highly distributed pieces of data provided by many different agents, in which such traditional methods can produce a great deal of overhead, hence reducing the scalability, efficiency and flexibility of the multiagent system. This work proposes the use of event tracing in multiagent systems, as an indirect interaction and coordination mechanism to improve the amount and quality of the information that agents can perceive from both their physical and social environment, in order to fulfill their goals more efficiently. In order to do so, this work presents an abstract model of a tracing system and an architectural design of such model, which can be incorporated to a typical multiagent platform.     

An ontology for commitments in multiagent systems:

Social commitments have long been recognized as an important concept for multiagent systems. We propose a rich formulation of social commitments that motivates an architecture for multiagent systems, which we dub spheres of commitment. We identify the key operations on commitments and multiagent systems. We distinguish between explicit and implicit commitments. Multiagent systems, viewed as spheres of commitment (SoComs), provide the context for the different operations on commitments. Armed with the above ideas, we can capture normative concepts such as obligations, taboos, conventions, and pledges as different kinds of commitments. In this manner, we synthesize ideas from multiagent systems, particularly the idea of social context, with ideas from ethics and legal reasoning, specifically that of directed obligations in the Hohfeldian tradition.     

分布式网络系统的任意预设时间分组一致

研究任意预设时间控制下的多智能体网络系统分组一致性问题.设计非零分组投影参数下任意预设时间控制协议,使得分布式网络系统在物理允许范围内的任意预设时间内迅速实现分组一致,该预设时间与系统参数和初始值都无关系.基于代数图论、李雅普诺夫稳定性和矩阵理论等,分别讨论无向和有向拓扑网络情形下,多智能体系统实现预设时间分组一致的充分条件.独轮车的多智能体系统仿真实验验证了所提方法的有效性.     

Self-organization of reflexive control systems

Translated from Kibernetika i Sistemnyi Analiz, No. 6, pp. 58–65, November–December, 1993.     

Adding security and trust to multiagent systems

Multiagent systems (MASs) are societies whose individuals are software delegatees (agents) acting on behalf of their owners or delegators (people or organizations). When deployed in an open network such as the Internet, MASs face some trust and security issues. Agents comeand go, and interact with strangers. Assumptions about security and general trustworthiness of agents and their deployers are inadequate in this context. In this paper, the design of a security infrastructure is presented applicable to MASs in general. This design addresses both security threats and trust issues. In this design, there are mechanisms for ensuring secure communication among agents and secure naming and resource location services. And two types of trusts are addressed: trust that agents will not misbehave and trust that agents are really delegatees of whom they claim to be. To establish the first type of trust, deployers of agents are made liable for the actions of their agents; to establish the second type of trust, it is proposed that agents prove that they know secrets that only their delegators know.     

Zeus: A toolkit for building distributed multiagent systems

The multiagent systems approach of knowledge- level cooperation between autonomous agents promises significant benefits to distributed systems engineering, such as enhanced interoperability, scalability, and reconfigurability. However, thus far, because of the innate difficulty of constructing multiagent systems, this promise has been largely unrealized. Hence there is an emerging desire among agent developers to move away from developing point solutions to point problems in favor of developing methodologies and toolkits for building distributed multiagent systems. This philosophy led to the development of the ZEUS Agent Building Toolkit, which facilitates the rapid development of collaborative agent applications through the provision of a library of agent- level components and an environment to support the agent-building process. The ZEUS toolkit is a synthesis of established agent technologies with some novel solutions to provide an integrated collaborative agent-building environment.     

Infrastructures for the environment of multiagent systems

The notion of environment is receiving an increasing attention in the development of multiagent applications. This is witnessed by the emergence of a number of infrastructures providing agent designers with useful means to develop the agent environment, and thus to structure an effective multiagent application. In this paper we analyse the role and features of such infrastructures, and survey some relevant examples. We endorse a general viewpoint where the environment of a multiagent system is seen as a set of basic bricks we call environment abstractions, which (i) provide agents with services useful for achieving individual and social goals, and (ii) are supported by some underlying software infrastructure managing their creation and exploitation. Accordingly, we focus the survey on the opportunities that environment infrastructures provide to system designers when developing multiagent applications.     

Formation and obstacle avoidance control for multiagent systems

This paper considers the problems of formation and obstacle avoidance for multiagent systems.The objective is to design a term of agents that can reach a desired formation while avoiding collision with obstacles.To reduce the amount of information interaction between agents and target,we adopt the leader-follower formation strategy.By using the receding horizon control (RHC),an optimal problem is formulated in terms of cost minimization under constraints.Information on obstacles is incorporated online as sensed in a limited sensing range.The communication requirements between agents are that the followers should obtain the previous optimal control trajectory of the leader to each update time.The stability is guaranteed by adding a terminal-state penalty to the cost function and a terminal-state region to optimal problem.Finally,simulation studies are provided to verify the effectiveness of the proposed approach.     

Coordination in multiagent systems and Laplacian spectra of digraphs

Constructing and studying distributed control systems requires the analysis of the Laplacian spectra and the forest structure of directed graphs. In this paper, we present some basic results of this analysis. We also discuss the application of these results published earlier to decentralized control and touch upon some problems of spectral graph theory.     

Soccer server: A tool for research on multiagent systems

This article describes Soccer Server, a simulator of the game of soccer designed as a benchmark for evaluating multiagent systems and cooperative algorithms. In real life, successful soccer teams require many qualities, such as basic ball control skills, the ability to carry out strategies, and teamwork. We believe that simulating such behaviors is a significant challenge for computer science, artificial intelligence, and robotics technologies. It is to promote the development of such technologies, and to help define a new standard problem for research, that we have developed Soccer Server. We demonstrate the potential of Soccer Server by reporting an experiment that uses the system to compare the performance of a neural network architecture and a decision tree algorithm at learning the selection of soccer play plans. Other researchers using Soccer Server to investigate the nature of cooperative behavior in a multiagent environment will have the chance to assess their progress at RoboCup-97, an international competition of robotic soccer to be held in conjunction with IJCAI-97. Soccer Server has been chosen as the official server for this contest.     

组合控制协议增强多智能体系统一致性

针对离散时间下基于切换拓扑多智能体系统一致性问题,设计出一种基于约束集虚拟邻居选取分布式一致性协议。该协议中,智能体采用通信扇区机制构造出虚拟邻居作为控制协议输入进行状态演化,并设计智能体调整因子的取值方式。在此基础上,智能体通过约束集保持初始通信拓扑的连接边来保证系统的连通性。最后,理论分析与大量仿真实例结合,与经典模型进行比较,验证了新的一致性协议的有效性,表明其可增强系统一致性,减少系统收敛的簇,并提高系统的一致性收敛速度。     

Consensus of multiagent systems based on disturbance observer

The objectives of this work are the development and design of disturbance observers (DO’s) for a team of agents that accomplish consensus on agents’ states in the presence of exogenous disturbances. A pinning control strategy is designed for a part of agents of the multiagent systems without disturbances, and this pinning control can bring multiple agents’ states to reaching an expected consensus value. Under the effect of the disturbances, nonlinear disturbance observers are developed for disturbances generated by an exogenous system to estimate the disturbances. Asymptotical consensus of the multiagent systems with disturbances under the composite controller can be achieved. Finally, by applying an example of multiagent systems with switching topologies and exogenous disturbances, the design of the parameters of DO’s are illuminated.     

On the supervisory control of multiagent product systems

In this note, we use the formal framework of multiagent (MA) product systems (introduced and developed in previous works) for the analysis of complex systems. The results of this note constitute a natural extension of the classical supervisory control results for scalar systems to the more general MA product system case. The notion of MA controllability is introduced and is shown to essentially constitute a necessary and sufficient condition for the synthesis of an MA supervisor.