ADK: An Agent Development Kit Based on a Formal Design Model for Multi-Agent Systems

The advent of multi-agent systems has brought us opportunities for the development of complex software that will serve as the infrastructure for advanced distributed applications. During the past decade, there have been many agent architectures proposed for implementing agent-based systems, and also a few efforts to formally specify agent behaviors. However, research on narrowing the gap between agent formal models and agent implementation is rare. In this paper, we propose a model-based approach to designing and implementing intelligent agents for multi-agent systems (MAS). Instead of using formal methods for the purpose of specifying agent behavior, we bring formal methods into the design phase of the agent development life cycle. Specifically, we use the formalism called agent-oriented G-net model, which is based on the G-net formalism (a type of high-level Petri net), to serve as the high-level design for intelligent agents. Based on the high-level design, we further derived the agent architecture and the detailed design for agent implementation. To demonstrate the feasibility of our approach, we developed the toolkit called ADK (Agent Development Kit) that supports rapid development of intelligent agents for multi-agent systems and we discuss the role of inheritance in agent-oriented development. As a potential solution for automated software development, we summarize the procedure to generate a model-based design of application-specific agents. Finally, to illustrate an application built on ADK, we present an air-ticket trading example.     

Distributed data mining on Agent Grid: Issues,platform and development toolkit

Centralized data mining techniques are widely used today for the analysis of large corporate and scientific data stored in databases. However, industry, science, and commerce fields often need to analyze very large datasets maintained over geographically distributed sites by using the computational power of distributed systems. The Grid can play a significant role in providing an effective computational infrastructure support for this kind of data mining. Similarly, the advent of multi-agent systems has brought us a new paradigm for the development of complex distributed applications. During the past decades, there have been several models and systems proposed to apply agent technology building distributed data mining (DDM). Through a combination of these two techniques, we investigated the critical issues to build DDM on Grid infrastructure and design an Agent Grid Intelligent Platform as a testbed. We also implement an integrated toolkit VAStudio for quickly developing agent-based DDM applications and compare its function with other systems.     

Organizational structures supported by agent-oriented methodologies

Agent technology is a software paradigm that permits to implement large and complex distributed applications. In order to assist the development of multi-agent systems, agent-oriented methodologies (AOM) have been created in the last years to support modelling more and more complex applications. Even though agents are perceived as autonomous entities that act according to some objectives, they are also members of a society, and have to exchange information with other agents and maintain some relationships at an organizational level. Modern AOMs should be able to capture and represent organizational structures, defining interaction and collaboration patterns between agents, their internal roles and dependencies between groups of agents. This paper analyses the most notable AOMs, paying attention to the support and possibilities that they offer for modelling organizational structures with different levels of complexity. This work can help developers to select the most appropriate methodology taking into account the social and organizational requirements of the multi-agent system to be deployed.     

多Agent系统可视化开发环境的设计与实现

多Agent系统是构造复杂的分布式软件的一种新方法,有广阔的应用前景。但设计多Agent系统难度很大,除了要考虑传统的分布式系统的所有问题外,还要考虑Agent的灵活性需求。为了支持多Agent系统的开发,提出并实现了一个可视化开发环境,用户可以从描述任务出发,经过一系列步骤,半自动化地生成多Agent系统,极大地减轻了编程负担。     

Agent-Based Simulation of Animal Behaviour

In the biological literature on animal behaviour, in addition to real experiments and field studies, also simulation experiments are a useful source of progress. Often specific mathematical modelling techniques are adopted and directly implemented in a programming language. Modelling more complex agent behaviours is less adequate using the usually adopted mathematical modelling techniques. The literature on AI and Agent Technology offers more specific methods to design and implement (also more complex) intelligent agents and agent societies on a conceptual level. One of these methods is the compositional multi-agent system design method DESIRE. In this paper it is shown how (depending on the complexity of the required behaviour) a simulation model for animal behaviour can be designed at a conceptual level in an agent-based manner. Different models are shown for different types of behaviour, varying from purely reactive behaviour to pro-active, social and adaptive behaviour. The compositional design method for multi-agent systems DESIRE and its software environment supports the conceptual and detailed design, and execution of these models. A number of experiments reported in the literature on animal behaviour have been simulated for different agent models.     

A retraining methodology for enhancing agent intelligence

Data mining has proven a successful gateway for discovering useful knowledge and for enhancing business intelligence in a range of application fields. Incorporating this knowledge into already deployed applications, though, is highly impractical, since it requires reconfigurable software architectures, as well as human expert consulting. In an attempt to overcome this deficiency, we have developed Agent Academy, an integrated development framework that supports both design and control of multi-agent systems (MAS), as well as “agent training”. We define agent training as the automated incorporation of logic structures generated through data mining into the agents of the system. The increased flexibility and cooperation primitives of MAS, augmented with the training and retraining capabilities of Agent Academy, provide a powerful means for the dynamic exploitation of data mining extracted knowledge. In this paper, we present the methodology and tools for agent retraining. Through experimented results with the Agent Academy platform, we demonstrate how the extracted knowledge can be formulated and how retraining can lead to the improvement – in the long run – of agent intelligence.     

基于政策自组织系统的软件agent体系结构及其实现

当前自组织系统软件工程面临的一个重要挑战,就是如何设计适宜的个体交互行为来满足自组织系统的宏观涌现需求。针对此问题,提出了一种基于政策的自组织多agent系统的开发方法,此方法通过政策调节引导agent的行为,以期在系统层面得到用户所需求的宏观涌现结果。开发这类系统的核心问题是如何构造系统中的软件agent,使得agent能够感知、理解系统政策,并在遵循政策的前提下实现行为的自主决策。提出了一种基于政策自组织多agent系统的软件agent体系结构,并基于该体系结构设计了运行机制及行为决策算法。通过软件方式实现了一个基于政策的自组织多agent系统开发平台原型,并通过案例实现说明了体系结构、运行机制的有效性。     

自适应系统软件传感器设计与实现

随着Internet的普及应用,越来越多的软件系统运行在开放的环境中,需要感知和适应环境的变化.如何支持这类复杂软件系统的开发和运行已经成为当前软件工程面临的一项重要挑战.针对自适应系统与其驻留环境的交互问题,将自适应系统中的软件实体抽象为自主Agent,提出了自主Agent感知环境变化的软件传感器及其与环境的动态关联思想,给出了软件传感器的设计和实现.不同于已有研究,将软件传感器视为一类特殊的软件Agent.最后通过案例分析展示了上述思想和技术的可行性和有效性.     

Supporting Controlled Experimentation with Testing Techniques: An Infrastructure and its Potential Impact

Where the creation, understanding, and assessment of software testing and regression testing techniques are concerned, controlled experimentation is an indispensable research methodology. Obtaining the infrastructure necessary to support such experimentation, however, is difficult and expensive. As a result, progress in experimentation with testing techniques has been slow, and empirical data on the costs and effectiveness of techniques remains relatively scarce. To help address this problem, we have been designing and constructing infrastructure to support controlled experimentation with testing and regression testing techniques. This paper reports on the challenges faced by researchers experimenting with testing techniques, including those that inform the design of our infrastructure. The paper then describes the infrastructure that we are creating in response to these challenges, and that we are now making available to other researchers, and discusses the impact that this infrastructure has had and can be expected to have. Editor: Forrest Shull and Natalia Juristo     

AN ACL FOR SPECIFYING FAULT-TOLERANT PROTOCOLS

Agent communication languages (ACLs) should allow the developer to adopt human-like communication mechanisms in agent programming, facilitating the development of distributed protocols in multi-agent systems (MASs). However, to implement robust protocols, ACLs should provide a way to deal with the failures of agents, as MASs are prone to the same failures that can occur in any distributed software system. In this paper, we address this issue showing how an asynchronous ACL that provides high-level mechanisms to deal with crash failures of agents can be effectively used to specify fault tolerant protocols.     

Reflections on the Nature of Multi-Agent Coordination and Its Implications for an Agent Architecture

The development of enabling infrastructure for the next generation of multi-agent systems consisting of large numbers of agents and operating in open environments is one of the key challenges for the multi-agent community.Current infrastructure support does not materially assist in the development of sophisticated agent coordination strategies. It is the need for and the development of such a high-level support structure that will be the focus of this paper. A domain-independent (generic) agent architecture is proposed that wraps around an agent's problem-solving component in order to make problem solving responsive to real-time constraints, available network resources, and the need to coordinate—both in the large and small—with problem-solving activities of other agents. This architecture contains five components, local agent scheduling, multi-agent coordination, organizational design, detection and diagnosis, and on-line learning, that are designed to interact so that a range of different situation-specific coordination strategies can be implemented and adapted as the situation evolves. The presentation of this architecture is followed by a more detailed discussion on the interaction among these components and the research questions that need to be answered to understand the appropriateness of this architecture for the next generation of multi-agent systems.     

Relating Requirements and Architectures: A Study of Data-Grids

The requirements and architecture of any complex software system are highly interdependent. We have studied the relationship between these two concerns in several data-Grid systems. Data-Grids are characterized by an infrastructure that focuses on the coordinated management of, and access to distributed data resources. We survey current data-Grid projects to demonstrate that a set of general requirements for data-Grid systems can be identified. Architectural styles are a way of highlighting design and engineering similarities between software systems. We consider the styles that are exhibited by current data-Grids and use a lightweight methodology to analyze how these styles support general requirements. Our conclusions provide guidelines to assist the data-Grid developer in making informed architectural choices.     

A framework for the design and automated implementation of communication aspects in multi-agent systems

This paper presents REFCON, a framework for the automated development of Agent Communication Contexts (ACCs) in multi-agent systems (MASs). ACCs are intended to capture the interaction requirements of a MAS.A formal specification framework is first presented, aimed at modelling an ACC as a set of rules for filtering and filling messages, based on their contents, and the names and roles of the exchanging agents. A XML-based specification language is then introduced, which encodes the specification formalism for the sake of its computer processing. Finally, an object-oriented software architecture capable of supporting ACC-based MAS development is presented.REFCON key characteristic is that it allows a seamless integration of ACC support (even) into an existing MAS, at run-time, independently of the agent platform used for the implementation. This is made possible by a layered software architecture based on computational reflection, a technology that allows transparent evolution and adaptation of existing systems. The REFCON framework is also dynamic, in the two-fold sense that it is capable of both adding new rules and handling multiple contexts, which it can easily switch among, at run-time. The ACC-based design of an example MAS for document sharing is briefly discussed, as a demonstration of the principles put forward.     

A formal framework for multi-agent systems analysis and design

Agent based computing is generally intended for modeling and implementation of distributed complex problems. Despite the existence of many applications, the problem of rational engineering of multi-agent systems remains complex and difficult. The purpose of this paper can be summarized within two claims. First, we aim at providing an approach that gives some guidelines for specifying and designing multi-agent systems. Secondly, we focus on the formalisms as a language for describing the models produced in each development process phases. These seem to be straightforward, while the development of multi-agent systems is still done, in most cases, without using methods and formal modeling such as those generally used in object oriented software. We illustrate this approach by specifying an example based upon a specific agent architecture.     

Development of a multi-agent-based distributed simulation platform for semiconductor manufacturing

Since the semiconductor manufacturing system is a large-scale complex system, it is difficult to solve complex problems in semiconductor manufacturing by the mathematical modeling method. This paper presents a multi-agent-based distributed simulation platform to support the extremely complex semiconductor manufacturing analysis. A multi-agent-based distributed simulation platform framework and a multi-agent collaborative control model are proposed to provide a flexible infrastructure and a multi-agent coordination mechanism in distributed environment for semiconductor manufacturing simulation. A multi-agent time synchronization model for distributed simulation is designed to keep events in the correct logical time order in simulation and steps of time synchronization are given. An interaction model and message formats are presented to describe how agents communicate with each other in simulation. The platform development and the design of graphical user interface are also exploited in this paper. Finally, evaluation of this multi-agent-based platform was illustrated with a case study. It indicates that the platform is effective in modeling and simulating the complex semiconductor manufacturing and provides the insights about how to improve the semiconductor manufacturing process with well targeted measures.     

飞机电源多Agent 预测与健康管理系统研究

针对复杂多任务的飞机电源预测与健康管理的需求,以状态维护开放系统体系结构OSA-CBM模型为标准架构,提出一种基于多Agent 的飞机电源故障预测与健康管理系统体系结构模型。结合原型系统开发实例,详细阐述了各Agent 的功能及相互关系。采用AUML 技术构建基于多Agent 的AEPHM系统模型,通过AUML 协议图描述了Agent 之间的主要交互活动。实践表明,该体系结构为航空机载设备预测与健康管理系统建设提供了一种新的设计开发模式。     

A GENERIC TIME MANAGEMENT SERVICE FOR DISTRIBUTED MULTI-AGENT SYSTEMS

Multi-agent systems are well suited for building large software systems. A great deal of these complex systems includes process flows that are concerned with time or are even time-critical. The activities of these process flows are often executed in distributed autonomous subsystems that have to be synchronized with respect to the superordinated task execution. To be able to build such systems and test their behavior adequately, it is often advantageous and sometimes necessary to simulate them in the run-up to their practical use. Testing and simulation of process flows within multi-agent systems requires synchronization of the participating agents with respect to the global simulation time. In this paper, a design proposal and a service implementation for time management is presented, which takes care of the special requirements imposed by multi-agent settings. This so-called time service is implemented as an FIPA-compliant agent, and can be used to couple heterogeneous subsystems implemented on different agent platforms.     

Agent系统的软件工程过程

Agent技术和多Agent系统是解决许多复杂、分布应用的有效途径。该文讨论了建立多Agent系统的软件工程方法,内容包括:如何给出多Agent系统的需求描述,这些描述如何转化为高效的实现形式,如何检查多Agent系统的实现与其描述一致等。并用一些实例进行了说明。     

基于多Agent系统的自调节及协同工作的组合投资模型

Agent技术特别是多Agent系统（MAS,Multi-Agent System）为解决人工智能等领域复杂问题提供了一个新途径,多Agent系统重点研究如何协调系统中的各个Agent的行为使其协同工作。针对多阶段组合投资问题,提出了一个基于多Agent系统的自调节及协同工作的组合投资策略模型。该模型系统中的各个Agent通过通讯共享知识,在求解问题的搜索空间中进行协同搜索,在更短的搜索步长内得到问题的解,极大地提高了系统性能。该模型具有不基于任何股票模型、时间复杂度低以及逼近最优投资策略速度较快等优点,实验证明具有一定的实际意义。     

JADE implemented mobile multi-agent based,distributed information platform for pervasive health care monitoring

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.