Coordination Tools for MAS Development and Deployment

One of the most critical issues in the engineering of multi-agent systems (MAS) is the inadequacy of the available tools for MAS development and deployment. As we assume interaction as a first-class issue in MAS, tools are particularly required to monitor and debug inter-agents aspects, such as interaction protocols, coordination policies, social norms, and environment constraints. Since we claim that the definition of such tools is a basic research issue, in this paper we aim to identify the main requirements for development and deployment tools within an effective agent infrastructure. Focusing on agent interaction aspects, we take tuple-based coordination infrastructures--in particular the TuCSoN technology and tools--as our reference, and discuss the role of tools in a simple case study: the development and deployment of a well-known agent interaction protocol, the Contract Net.     

Multiagent systems and information retrieval our experience with X.MAS

Autonomous agents and multiagent systems have been successfully applied to a number of problems and have been largely used in different application fields. In particular, in this paper we are interested in information retrieval. In fact, in this field multiagent solutions are very useful and effective since they decouple the problem in a network of software agents that interact to solve problems that are beyond the individual capabilities or knowledge. In so doing, multiagent systems allow to overwhelm typical problems of single agent and centralized approaches. To discuss the lesson learnt in using the multiagent technology in the field of information retrieval, in this paper, we present our experience in using X.MAS, a generic multiagent architecture aimed at retrieving, filtering and reorganizing information according to user interests. To this end, after presenting X.MAS, we illustrate six applications built upon it. Our conclusion is that multiagent technology is quite effective to design and realize concrete information retrieval applications.     

Design and implementation of a multiagent stock trading system

Stock trading is one of the key items in an economy and estimating its behavior and taking the best decision in it are among the most challenging issues. Solutions based on intelligent agent systems are proposed to cope with those challenges. Agents in a multiagent system (MAS) can share a common goal or they can pursue their own interests. That nature of MASs exactly fits the requirements of a free market economy. Although existing studies include noteworthy proposals on agent‐based market simulation and researchers discuss theoretical design issues of agent‐based stock exchange systems, unfortunately only a very few of the studies consider exact development and implementation of multiagent stock trading systems within the software engineering perspective and guides to the software engineers for constructing such software systems starting from scratch. To fill this gap, in this paper, we discuss the development of a multiagent‐based stock trading system by taking into consideration software design according to a well‐defined agent oriented software engineering methodology and implementation with a widely‐used MAS software development framework. Each participant in the system is first designed as belief–desire–intention agents with their facts, goals, and plans, and then belief–desire–intention reasoning and behavioral structure of the designed agents are implemented. Lessons learned during design and development within the software engineering perspective and evaluation of the implemented multiagent stock exchange system are also reported. Copyright © 2011 John Wiley & Sons, Ltd.     

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.     

基于OPM/MAS 的钢铁企业多agent 生产调度模型

现有的面向agent建模方法在统一性、灵活性、交互能力、逻辑验证能力等方面存在很多不足,阻碍了多agent系统的研究和设计.为此,引入对象过程/多智能体系统(OPM/MAS)的建模方法,将系统的功能、结构和动态行为集成在统一的模型中,用图形和自然语言共同表达复杂系统的抽象概念,可进行逻辑验证,并具有灵活性强、表意清晰等优势.通过在钢铁企业生产调度中的应用,验证了OPM/MAS在多agent等复杂系统建模中的有效性.     

Layered approach to learning client behaviors in the robocup soccer server

In the past few years, multiagent systems (MAS) have emerged as an active subfield of artificial intelligence (AI). Because of the inherent complexity of MAS, there is much interest in using machine learning (ML) techniques to help build multiagent systems. Robotic soccer is a particularly good domain for studying MAS and multiagent learning. Our approach to using ML as a tool for building Soccer Server clients involves layering increasingly complex learned behaviors. In this article, we describe two levels of learned behaviors. First, the clients learn a low-level individual skill that allows them to control the ball effectively. Then, using this learned skill, they learn a higher level skill that involves multiple players. For both skills, we describe the learning method in detail and report on our extensive empirical testing. We also verify empirically that the learned skills are applicable to game situations.     

A Virtual World Grammar for automatic generation of virtual worlds

Hybrid systems such as those that combine 3D virtual worlds and organization based multiagent systems add new visual and communication features for multiuser applications. The design of such hybrid and dynamic systems is a challenging task. In this paper, we propose a system that can automatically generate a 3D virtual world (VW) from an organization based multiagent system (MAS) specification that establishes the activities participants can engage on. Both shape grammar and virtual world paradigms inspired us to propose a Virtual World Grammar (VWG) to support the generation process of a virtual world design. A VWG includes semantic information about both MAS specification and shape grammar elements. This information, along with heuristics and validations, guides the VW generation producing functional designs. To support the definition and execution of a Virtual World Grammar, we have developed a so named Virtual World Builder Toolkit (VWBT). We illustrate this process by generating a 3D visualization of a virtual institution from its specification.     

SOFTWARE AND PERFORMANCE MEASURES FOR EVALUATING MULTI-AGENT FRAMEWORKS

ABSTRACT

Nowadays, multi-agent frameworks allow to implement very complex systems by means of agent technology. However, this complexity makes it more difficult to evaluate software and runtime characteristics of multiagent systems (MAS). Our aim is to define and study some quantitative measures to measure MAS aspects like development time, reusability, scalability, etc. These measures could be used by engineers to guide the selection among several MAS frameworks. Our study has been carried out in several MAS frameworks like JADE, JATLite, SkeletonAgent, and ZEUS, which have been used to build a MAS application for news retrieval.     

Multiagent Systems: A Survey from a Machine Learning Perspective

Distributed Artificial Intelligence (DAI) has existed as a subfield of AI for less than two decades. DAI is concerned with systems that consist of multiple independent entities that interact in a domain. Traditionally, DAI has been divided into two sub-disciplines: Distributed Problem Solving (DPS) focuses on the information management aspects of systems with several components working together towards a common goal; Multiagent Systems (MAS) deals with behavior management in collections of several independent entities, or agents. This survey of MAS is intended to serve as an introduction to the field and as an organizational framework. A series of general multiagent scenarios are presented. For each scenario, the issues that arise are described along with a sampling of the techniques that exist to deal with them. The presented techniques are not exhaustive, but they highlight how multiagent systems can be and have been used to build complex systems. When options exist, the techniques presented are biased towards machine learning approaches. Additional opportunities for applying machine learning to MAS are highlighted and robotic soccer is presented as an appropriate test bed for MAS. This survey does not focus exclusively on robotic systems. However, we believe that much of the prior research in non-robotic MAS is relevant to robotic MAS, and we explicitly discuss several robotic MAS, including all of those presented in this issue.     

仿真机器人足球学习方法研究综述

仿真机器人足球赛是近几年在国际上迅速开展起来的高技术对抗活动，虽然历史不长，但由于它集高新技术、娱乐比赛于一体，所以引起了人们的广泛关注和极大兴趣。作为多智能体系统研究的重要手段，许多研究者从不同的侧面对该项技术进行了研究并取得了一定的成果。对仿真机器人足球系统的研究，目前包括系统组织结构设计、多智能体结构及协调机制研究、智能体技能学习和对手模型预测等内容。该文从多智能体学习和协作的角度对有关机器人足球的学习方法进行了介绍和评述。     

A platform-independent metamodel for multiagent systems

Various agent-oriented methodologies and metamodels exist to design and develop multiagent systems (MAS) in an abstract manner. Frequently, these frameworks specialise on particular parts of the MAS and only few works have been invested to derive a common standardisation. This limits the impact of agent-related systems in commercial applications. In this paper, we present a metamodel for agent systems that abstracts from existing agent-oriented methodologies, programming languages, and platforms and could thus be considered as platform-independent. This metamodel defines the abstract syntax of a proposed domain-specific modelling language for MAS that is currently under development and provides furthermore the base to generate code out of the generated designs. This is done by applying the principles of model-driven development (MDD) and providing two model transformations that allow transforming the generated models into textual code that can be executed with JACK and JADE.     

Using bayesian networks to model agent relationships

An agent-society of the future is envisioned to be as complex as a human society. Just like human societies, such multiagent systems (MAS) deserve an in-depth study of the dynamics, relationships, and interactions of the constituent agents. An agent in a MAS may have only approximate a priori estimates of the trustworthiness of another agent. But it can learn from interactions with other agents, resulting in more accurate models of these agents and their dependencies together with the influences of other environmental factors. Such models are proposed to be represented as Bayesian or belief networks. An objective mechanism is presented to enable an agent elicit crucial information from the environment regarding the true nature of the other agents. This mechanism allows the modeling agent to choose actions that will produce guaranteed minimal improvement of the model accuracy. The working of the proposed maxim in entropy procedure is demonstrated in a multiagent scenario.     

多智能体技术及其在虚拟企业伙伴选择中的应用

研究了一种多智能体的体系结构及其实现技术。并实现了基于这种智体技术的虚拟企业伙伴选择原型系统。证明智能体技术在构建虚拟组织信息系统中的有效性。     

Distributed problem solving in multiagent systems: a spring net approach

This paper presents a new spring net approach for distributed problem solving in MAS. Distributed artificial intelligence consists of distributed problem solving and multi-agent systems. We extend such specialized DPS and MASs to a general MAS, such that an agent may make a trade-off between selfishness and unselfishness, thus adjusting its own personality and autonomy. This alternative to traditional approaches can deal with a variety of complicated social interactions and autonomous behaviors occurring in multiagent systems.     

车间调度中的数据挖掘技术研究

基于Multi-Agent System（MAS）的人机合作技术适合于解决复杂调度问题。为了使人与机能够更好地合作来完成高效、准确的车间调度,引入C4.5算法,建立并实现了基于机器学习和MAS的人机合作车间调度系统仿真模型。在Java环境下,以Weka、JADE为开发平台,以Eclipse为开发工具,Access为后台数据库,完成了系统的开发。通过实例仿真和结果分析,运用机器学习算法动态调度的结果稍优于最佳的静态调度结果,证明了系统的正确性和优越性。     

面向自动文摘的多Agent系统中的协调算法研究

为了解决自动文摘系统所面临的领域通用性和文摘质量的矛盾,提出了建造面向自动文摘的多Aent系统（MAS／ABS)的方案。建造这样的系统,有两个关键问题：建立什么样的系统模型和选择什么样的协调算法。给出了在Internet环境下面向自动文摘的多Agent系统模型,提出了3种协调算法。在仿真的基础上分析了系统性能,对3种协调算法进行了比较研究,并得到了在一定负载下面向各个领域合适的文摘Agent数目。     

MUSIC-MAS: Modeling a harmonic composition system with virtual organizations to assist novice composers

Many music students today experience difficulties in composing melodies without a prior harmonical guide. While harmony can be helpful in creating a melody the generation of harmony is challenging due to the many factors that must be taken into account, such as style, harmonic functions, musical consonance or aesthetics. Although various solutions have been proposed in the past, our study employs a different expert solution based on virtual organizations to make musical harmonies, which can assist novice improvisers and/or composers. The virtual organizations are implemented with Multi-Agent System (MAS) using PANGEA (Platform for Automatic coNstruction of orGanizations of intElligent Agents), a platform to develop different multiagent systems. The main goal is to simulate an expert multiagent system that can compose harmony following specific rules. To do so, the Harmony Search Algorithm is implemented as the main behavior of the composer agent, and adapted to a Belief-Desire-Intention architecture. The application of a VO has not been previously used in the development of this kind of expert system in music. We measured the quality of the music obtained, by minimizing a mathematical function. Additionally, we developed an evaluation test that positively validates the musical results from the perspective of consonance and usefulness of the composers.     

A new multi-agent system framework for tacit knowledge management in manufacturing supply chains

Participating members in a manufacturing supply chain (MSC) usually make use of individual knowledge for making independent decisions. Recent research, however, indicates that there is a need to handle such distributed knowledge in an integrated manner, especially under uncertain and fast changing environments. A multiagent system (MAS), a branch of distributed artificial intelligence, is a contemporary modelling technique for a distributed system like MSCs in the manufacturing domain. However recent researches indicate that MAS approaches have not adequately addressed the role of sharing tacit knowledge (TK) on MSC performance. This paper, therefore, aims to propose a framework that utilizes MAS techniques with a corresponding TK sharing mechanism dedicated to MSCs. We performed some experiments to simulate the proposed approach. The results showed significant improvements when comparing the proposed approach with another conventional MAS model. The results establish a starting point for researchers interested in enhancing MSC performance using TK management approach, and for managers of MSC to focus on the essentials of sharing TK.     

Evaluating software engineering techniques for developing complex systems with multiagent approaches

Context

Multiagent systems (MAS) allow complex systems to be developed in which autonomous and heterogeneous entities interact. Currently, there are a great number of methods and frameworks for developing MAS. The selection of one or another development environment is a crucial part of the development process. Therefore, the evaluation and comparison of MAS software engineering techniques is necessary in order to make the selection of the development environment easier.

Objective

The main goal of this paper is to define an evaluation framework that will help in facilitating, standardizing, and simplifying the evaluation, analysis, and comparison of MAS development environments. Moreover, the final objective of the proposed tool is to provide a repository of the most commonly used MAS software engineering methods and tools.

Method

The proposed framework analyzes methods and tools through a set of criteria that are related to both system engineering dimensions and MAS features. Also, the support for developing organizational and service-oriented MAS is studied. This framework is implemented as an online application to improve its accessibility.

Results

In this paper, we present Masev, which is an evaluation framework for MAS software engineering. It allows MAS methods, techniques and environments to be analyzed and compared. A case study of the analysis of four methodologies is presented.

Conclusion

It is concluded that Masev simplifies the evaluation and comparison task and summarizes the most important issues for developing MAS, organizational MAS, and service-oriented MAS. Therefore, it could help developers to select the most appropriate MAS method and tools for developing a specific system, and it could be used for MAS software engineering developers to detect and deficiencies in their methods and tools. Also, developers of new tools can understand this application as a way to publish their tools and demonstrate what their contributions are to the state of the art.