The Advantages of Designing Adaptive Business Agents Using Reputation Modeling Compared to the Approach of Recursive Modeling

Adaptive business agents operate in electronic marketplaces, learning from past experiences to make effective decisions on behalf of their users. How best to design these agents is an open question. In this article, we present an approach for the design of adaptive business agents that uses a combination of reinforcement learning and reputation modeling. In particular, we take into account the fact that multiple selling agents may offer the same good with different qualities, and that selling agents may alter the quality of their goods. We also consider the possibility of dishonest agents in the marketplace. Our buying agents exploit the reputation of selling agents to avoid interaction with the disreputable ones, and therefore to reduce the risk of purchasing low value goods. We then experimentally compare the performance of our agents with those designed using a recursive modeling approach. We are able to show that agents designed according to our algorithms achieve better performance in terms of satisfaction and computational time and as such are well suited for the design of electronic marketplaces.     

Purpose-Based Expert Finding in a Portfolio Management System

Most of the research in the area of expert finding focuses on creating and maintaining centralized directories of experts' profiles, which users can search on demand. However, in a distributed multiagent-based software environment, the autonomous agents are free to develop expert models or model fragments for their own purposes and from their viewpoints. Therefore, the focus of expert finding is shifting from the collection at one place as much data about a expert as possible to accessing on demand from various agents whatever user information is available at the moment and interpreting it for a particular purpose. This paper outlines purpose-based expert modeling as an approach for finding an expert in a multiagent portfolio management system in which autonomous agents develop expert agent models independently and do not adhere to a common representation scheme. This approach aims to develop taxonomy of purposes that define a variety of context-dependent user modeling processes, which are used by the users' personal agents to find appropriate expert agents to advise users on investing strategies.     

A multiagent architecture for fuzzy modeling

In this paper a hybrid learning system that combines different fuzzy modeling techniques is being investigated. In order to implement the different methods, we propose the use of intelligent agents, which collaborate by means of a multiagent architecture. This approach, involving agents which embody the different problem solving methods, is a potentially useful strategy for enhancing the power of fuzzy modeling systems. ©1999 John Wiley & Sons, Inc.     

基于Multi-agent的建模仿真方法研究

基于Multi-agent的建模仿真方法侧重于研究多个主体之间的相互作用,为描述和研究复杂系统提供了更加符合现实和更加有效的建模框架,是研究复杂系统的一个有效途径.简要介绍了复杂适应系统理论,阐述了该建模仿真方法的仿真平台,指出了该建模仿真方法的主要应用领域.     

SITUATED CELLULAR AGENTS APPROACH TO CROWD MODELING AND SIMULATION

The article describes a multi-agent approach to crowd modeling and simulation. After a brief introduction of the Situated Cellular Agents model, the guidelines to the crowd modeling approach is introduced as a way to support the communication among the different actors that are part of the simulation project team. The approach is then applied to describe a complex scenario providing a blend of competitive and cooperative behavior for pedestrian agents: an underground station. A module supporting the effective 3D visualization of simulated crowd dynamics is finally introduced, as an instrument for the communication of simulation results to decision makers and nonexperts in crowd phenomena.     

智能代理及其在通信领域中的应用

智能代理方法作为分布式人工智能的重要组成部分,被认为有可能为一类具有时间、空间或功能分布性的系统提供建模、分析和控制的方法。智能代理方法具有广阔的应用前景,尤其在具有侵分布性的和要求协作的环境中。本文回顾了智能代理方法及其研究的主要问题,并讨论该方法在通信领域中的应用。     

Design, development and validation of an agent-based model of electronic auctions

This paper presents the design, development and validation methodology of an agent-based computational model of the B2C electronic auction marketplace. It aims at a comprehensive understanding of the varied issues governing a B2C electronic auction, incorporating the behavior of all relevant agents such as the auctioneer, the consumer and the retailer; and the environment in which these agents operate and interact. In contrast with conventional methods, agent based modeling employs a bottom-up modeling approach where behaviors of individual agents and rules for their interaction, specified at the micro level, give rise to emergent macro level phenomenon. The development methodology should ensure that agent models are aligned with theory, current knowledge of the field and observed phenomena, and output validity of the model also needs to be ascertained. Beginning with a general introduction to agent based computational modeling, this paper formalizes this alignment and validation methodology and elaborates each step, noting the rationale and means for achieving these. The manner in which this process was used in modeling B2C auctions is then described.     

Velocity-based modeling of physical interactions in dense crowds

We present an interactive algorithm to model physics-based interactions in dense crowds. Our approach is capable of modeling both physical forces and interactions between agents and obstacles, while also allowing the agents to anticipate and avoid upcoming collisions during local navigation. We combine velocity-based collision-avoidance algorithms with external physical forces. The overall formulation produces various effects of forces acting on agents and crowds, including balance recovery motion and force propagation through the crowd. We further extend our method to model more complex behaviors involving social and cultural rules. We use finite-state machines to specify a series of behaviors and demonstrate our approach on many complex scenarios. Our algorithm can simulate a few thousand agents at interactive rates and can generate many emergent behaviors.     

Modeling and Optimal Centralized Control of a Large-Size Robotic Population

This paper describes an approach to the modeling and control of multiagent populations composed of a large number of agents. The complexity of population modeling is avoided by assuming a stochastic approach, under which the agent distribution over the state space is modeled. The dynamics of the state probability density functions is determined, and a control problem of maximizing the probability of robotic presence in a given region is introduced. The Minimum Principle for the optimal control of partial differential equations is exploited to solve this problem, and it is applied to the mission control of a simulated large robotic population     

A systematic approach to evaluating domain-specific modeling language environments for multi-agent systems

Multi-agent systems (MASs) include multiple interacting agents within an environment to provide a solution for complex systems that cannot be easily solved with individual agents or monolithic systems. However, the development of MASs is not trivial due to the various agent properties such as autonomy, responsiveness, and proactiveness, and the need for realization of the many different agent interactions. To support the development of MASs various domain-specific modeling languages (DSMLs) have been introduced that provide a declarative approach for modeling and supporting the generation of agent-based systems. To be effective, the proposed DSMLs need to meet the various stakeholder concerns and the related quality criteria for the corresponding MASs. Unfortunately, very often the evaluation of the DSML is completely missing or has been carried out in idiosyncratic approach. If the DSMLs are not well defined, then implicitly this will have an impact on the quality of the MASs. In this paper, we present an evaluation framework and systematic approach for assessing existing or newly defined DSMLs for MASs. The evaluation is specific for MAS DSMLs and targets both the language and the corresponding tools. To illustrate the evaluation approach, we first present SEA_ML, which is a model-driven MAS DSML for supporting the modeling and generation of agent-based systems. The evaluation of SEA_ML is based on a multi-case study research approach and provides both qualitative evaluation and quantitative analysis. We report on the lessons learned considering the adoption of the evaluation approach as well as the SEA_ML for supporting the generation of agent-based systems.     

An organism-oriented modeling approach to support the analysis and design of intelligent manufacturing systems

In this paper a generic macroscopic object, termed an organism, is introduced. An organism defines a high-level modeling object that has the capabilities for organizational networking, standardization or characteristics specifications, decoupling of editing and visualization as well as temporal management. Organism-oriented models inherit from their parent object-oriented and object/agent-oriented models a simplified representation of the manufacturing entities as well as a capacity for many levels of abstraction. Moreover, the organism-oriented modeling approach enriches these models by not only considering basic manufacturing objects and agents, but also the fact that each of these objects and agents may itself be an organization and also part of one or several organizations. The paper first surveys some of the current approaches used for modeling and analysing manufacturing systems: structured analysis, Petri nets, object and object/ agent models. The object model behind the organism-oriented modeling approach is then presented and its application to a manufacturing case is illustrated.     

基于代理和BPEL4WS的Web服务合成与实现

Web服务的交互和实现被推荐通过软件代理来实现.Web服务目前还不能很好地支持动态、自适应的服务组合和分布式业务流程.软件代理在建模、知识表达和交互等技术上的优势,能够强化Web服务的交互和动态应用能力.基于代理和面向流程建模的BPEL4WS,可以实现Web服务面向业务应用的合成与执行,支持多个协同的业务流程及其动态配置.系统分析了代理、BPEL4WS和Web服务整合的技术与实现方案,利用JADE平台开发了相关的测试模型,并且以网上拍卖为案例,验证了所提方案及实现.     

Multi-Agent Multi-User Modeling in I-Help

This paper describesthe user modeling approach applied in I-Help, a distributed multi-agent based collaborative environment for peer help. There is a multitude of user modeling information in I-Help, developed by the various software agents populating the environment. These ‘user model fragments’ have been created in a variety of specific contexts to help achieve various goals. They are inherently inconsistent with one another and reflect not only characteristics of the users, but also certain social relationships among them. The paper explores some of the implications of multi-agent user modeling in distributed environments.     

基于Agent的建模与仿真概述

基于Agent的建模与仿真(ABMS)是研究复杂系统的有效途径和建模仿真方法学,足当前最具有活力、有所突破的仿真方法学,已经成为系统仿真领域的一个新的研究方向.全面总结和阐述了基于Agent的建模与仿真的相关理论基础和概念,包括CAS理论,ABMS中Agent的概念、结构;阐述了ABMS的原理(简单规则导致复杂的行为)与研究步骤;总结了ABMS的主要应用领域,包括经济领域、社会科学领域和军事领域;慨述了ABMS软件开发平台和工具包,给出了ABMS开发方法;给出了互联网上关于ABMS的的资源链接.因而有利于全面认识、应用和研究ABMS.     

A multi-agent methodology for multi-level modeling of mechatronic systems

Mechatronic design aims to integrate the models developed during the mechatronic design process, in order to be able to optimize the overall mechatronic system performance. A lot of work has been done in the last few years by researchers and software developers to achieve this objective. However, the level of integration does not yet meet the purposes of mechatronic system designers, particularly when dealing with modeling changes. Therefore, new methodologies are required to manage the multi-view complexity of mechatronic design. In this paper, we propose a multi-agent methodology for the multi-abstraction modeling issue of mechatronic systems. The major contribution deals with proposing a new method for the decomposition of the multi-level design into agents linked with relationships. Each agent is representing an abstraction level and both agent and relationships are managed with rules. By considering an application to a piezoelectric energy harvesting system, we show how we associate agents, rules and inter-level relationships to multi-abstraction modeling. We also show how modeling errors are identified using this approach.     

基于Agent的信息过程建模方法

文中提出了一种基于ａｇｅｎｔ的信息过程建模方法。该方法视客观世界中有信息处理能力的自主实体为ａｇｅｎｔ，先描述参与过程的ａｇｅｎｔ，再以ａｇｅｎｔ为中心收集过程的其它信息来建立过程模型。这种方法能明确地描述ａｇｅｎｔ的组织结构与事务的关联，并通过描述系统的状态变化来反映过程的动态变化，较好地反映了信息过程的动态特性。     

Merging deductive and inductive reasoning for processing textual descriptions of inter-human conflicts

We report on a novel approach to modeling a dynamic domain with limited knowledge. A domain may include participating agents where we are uncertain about motivations and decision-making principles of some of these agents. Our reasoning setting for such domains includes deductive, inductive, and abductive components. The deductive component is based on situation calculus and describes the behavior of agents with complete information. The machine learning-based inductive and abductive components involve the previous experience with the agents, whose actions are uncertain to the system. Suggested reasoning machinery is applied to the problem of processing customer complaints in the form of textual messages that contain a multiagent conflict. The task is to predict the future actions of an opponent agent to determine the required course of action to resolve a multiagent conflict. This study demonstrates that the hybrid reasoning approach outperforms both stand-alone deductive and inductive components. Suggested methodology reflects the general situation of reasoning in dynamic domains in the conditions of uncertainty, merging analytical (rule-based) and analogy-based reasoning.     

多Agent系统分布式问题求解的代数模型方法(Ⅰ): 社会行为、社会局势和社会动力学

该组论文提出一种新的代数模型方法，用于多Agent系统超分布超并行社会智能问题求解，该方法通过社会动力学和社会智能，统一地处理各种复杂的并行的社会行为，用于求解用常规方法难以处理的许多社会交互问题，本文是组合论文中第一篇，提出多Agent系统分布式问题求解的代数模型结构，讨论多Agent系统中典型社会行为模式及其性质，建立形式化描述，同时也论述了代数模型中的社会局势和社会动力学。     

A systolic parallel simulation system for dynamic traffic assignment: SPSS-DTA

This paper presents a new approach to solve dynamic traffic assignment problems. The approach employs a mixed method of real-time simulation and off-line optimization. The fundamental approach to the simulation is systolic parallel processing based on autonomous agent modeling. Agents continuously act on their own initiatives and access to database to get the status of the simulation world. In particular, existing models and algorithms were incorporated in designing the behavior of relevant agents such as car-following and headway distribution. Simulation is based on predetermined routes between centroids that are computed off-line by a conventional optimal path-finding algorithm such as the Frank-Wolf algorithm. Iterating the cycles of optimization and simulation, the proposed system will provide a practical and valuable traffic assignment. Gangnam-Gu district in Seoul, Korea is selected as the target area for the modeling. It is expected that real-time traffic assignment services can be provided on the Internet soon.     

Integration in industrial automation based on multi-agent systems using cultural algorithms for optimizing the coordination mechanisms

Integration in industrial automation can be approached from the theory of Distributed Artificial Intelligence. One approach is the modeling of different production units by agents that interact through interaction protocols, which are implemented following a coordination mechanism. Under this approach, integration in automation can be achieved through the optimization of implicit interactions in such mechanisms. This paper presents a strategy for integrating industrial processes based on Multi-Agent Systems (MAS), which consists of optimizing coordination mechanisms that implement conversations between agents, by using cultural algorithms. The cultural algorithm uses formal models of interaction protocols between agents, such as auction and tender, and the integration scheme comes from automation architectures based on MAS, to which their interactions are optimized. The proposed scheme enables data and service-oriented integration. The proposed strategy is applied in two industrial case studies related to the oil production process.