基于博弈分析的自动协商系统

自动协商作为一个热点已经研究了很多年。大多数研究工作都着重于研究独立协商应用的抽象和理论模型,而对于实际算法的应用性只做了很少的工作。主要提出了一种基于博弈论的比较有效的协商模型来解决协商中的冲突。在该模型中利用遗传算法进行策略优化,而利用另外一个算法对已有的No-Fear-of-Deviation（NFD）算法进行了改进。     

A negotiation methodology for multidisciplinary collaborative product design

The collaborative design of a complicated mechanical product often involves conflicting multidisciplinary objectives, thus one key problem is conflict resolution and coordination among the different disciplines. Since the characteristics such as cooperative competition, professional dependence, compromise, overall utility and so on exist in multidisciplinary collaborative design (MCD), an effective way to gradually eliminate the conflicts among the multiple disciplines and reach an agreement is the negotiation by which a compromise solution that satisfies all parties is got. By comprehensively analyzing the characteristics in MCD and considering the benefit equilibrium among discipline individuals and team, a negotiation strategy is presented, which maximize the union satisfaction degree of system overall objective under the premise of ensuring the higher satisfaction degree level of each discipline’s local objective. A design action of a discipline is abstractly expressed as a concession in the negotiation strategy, and a negotiation model used for MCD is generated by establishing the relation between concession and satisfaction degree. By the relation between satisfaction degree and objective function, the mapping relationship between satisfaction degree domain and physical domain is built to get the design solution. A negotiation process is planned, and a negotiation system framework is designed to support the negotiation among multiple disciplines and assist the different disciplines rapidly reach a consistent compromise solution. A design example of automotive friction clutch is given to illustrate the proposed method.     

A multi-agent platform for content-based image retrieval

Efficient and possibly intelligent image retrieval is an important task, often required in many fields of human activity. While traditional database indexing techniques exhibit a remarkable performance in textual information retrieval current research in content-based image retrieval is focused on developing novel techniques that are biologically motivated and efficient. It is well known that humans have a remarkable ability to process visual information and to handle the volume and complexity of such information quite efficiently. In this paper, we present a content-based image retrieval platform that is based on a multi-agent architecture. Each agent is responsible for assessing the similarity of the query image to each candidate image contained in a collection based on a specific primitive feature and a corresponding similarity criterion. The outputs of various agents are integrated using one of several voting schemes supported by the system. The system’s performance has been evaluated using various collections of images, as well as images obtained in specific application domains such as medical imaging. The initial evaluation has yielded very promising results.

A multi-agent system for distributed multi-project scheduling: An auction-based negotiation approach

Simultaneously running multiple projects are quite common in industries. These projects require local (always available to the concerned project) and global (shared among the projects) resources that are available in limited quantity. The limited availability of the global resources coupled with compelling schedule requirements at different projects leads to resource conflicts among projects. Effectively resolving these resource conflicts is a challenging task for practicing managers. This paper proposes a novel distributed multi-agent system using auctions based negotiation (DMAS/ABN) approach for resolving the resource conflicts and allocating multiple different types of shared resources amongst multiple competing projects. The existing multi-agent system (MAS) using auction makes use of exact methods (e.g. dynamic programming relaxation) for solving winner determination problem to resolve resource conflicts and allocation of single unit of only one type of shared resource. Consequently these methods fail to converge for some multi-project instances and unsuitable for real life large problems. In this paper the multi-unit combinatorial auction is proposed and winner determination problem is solved by efficient new heuristic.The proposed approach can solve complex large-sized multi-project instances without any limiting assumptions regarding the number of activities, shared resources or the number of projects. Additionally our approach further allows to random project release-time of projects which arrives dynamically over the planning horizon. The DMAS/ABN is tested on standard set of 140 problem instances. The results obtained are benchmarked against the three state-of-the-art decentralized algorithms and two existing centralized methods. For 82 of 140 instances DMAS/ABN found new best solutions with respect to average project delay (APD) and produced schedules on an average 16.79% (with maximum 57.09%) lower APD than all the five methods for solving the same class of problems.     

A multi-agent intelligent system for efficient ERP maintenance

The Enterprise Resource Planning (ERP) system is an enterprise-wide integrated software package designed to uphold the highest quality standards of business process. However, for the time being, when the business condition has been changed, the system may not guarantee that the process embedded in ERP is still best. Moreover, since the ERP system is very complex, maintaining the system by trial and error is very costly. Hence, this paper aims to construct a support system that adjusts ERP system to environmental changes. To do so, we adopt multi-agent intelligent technology that enables autonomous cooperation with one another to monitor ERP databases and to find any exceptional changes and then analyze how the changes will affect ERP performance. Moreover, Petri net is applied to manage the complexity and dynamics of agents’ behavior. To show the feasibility of the idea, a prototype agent system, ERP/PN, is proposed and an experiment is conducted.     

基于多代理的供应链协同生产计划模型

供应链是由分布在全球的供应商、制造商、仓库、分销中心和零售商组成的复杂网络。其生产计划具有分布性,自治性,同步性和开放性等特点,使得传统的生产计划方法已经不能适应供应链的计划需求。在分析了多代理技术和供应链系统生产计划特点的基础上,采用智能代理封供应链系统的功能实体和物理实体进行封装,提出了一个基于多代理的供应链系统网络模型,并构建了基于多智能代理的生产计划运行模式。该生产计划模型分为三层：全局生产计划,企业内部子生产计划和各个任务的详细生产计划。它突破了传统生产计划的局限性,从全局规划的角度来整合供应链上的所有资源,消除了不同企业子生产计划所产生的冲突和差异。很好的体现了供应链系统信息共享和资源共享的原则。     

A fuzzy-based negotiation approach for collaborative planning in manufacturing supply chains

The coordination of the planning operations across the manufacturing supply chains (MSC) is considered as a major component of supply chain management. As centralized coordination requires relevant information sharing, alternative approaches are needed to synchronize production plans between partners of MSC characterized by decentralized decision making systems with limited information sharing. In this paper, a bi-level fuzzy-based negotiation approach is proposed in order to model collaborative planning between MSC partners. During negotiation, each manufacturer is optimizing a bi-objective planning model. In order to generate optimal production plans, a genetic algorithm is used. To evaluate the exchanged proposals and the satisfaction degree of each partner, the fuzzy logic approach is adopted in the both negotiation levels. The main result of the developed approach consists in a collaborative decision making mechanism allowing the MSC partners to define their optimal production plans while considering the whole negotiating process with the pre-negotiation and post-negotiation stages. Computational tests done for different MSC structures show the effectiveness of the proposed mechanism, which ensures the satisfaction of the manufacturers and the optimality of the final solution. By comparing the results with the ones obtained considering a centralized planning approach, it is shown that the developed negotiation mechanism yields to near optimal solutions with insignificant gaps from the global optimal solutions.     

A virtual collaborative maintenance architecture for manufacturing enterprises

This paper presents a virtual collaborative maintenance architecture aimed at improving the performance of manufacturing systems. The proposed architecture incorporates maintenance elements such as operational reliability, maintenance economics, human factors in maintenance, maintenance program, and maintenance optimization in a virtual collaborative architecture. An analytical model is proposed to measure the relative performance of the proposed virtual collaborative architecture as well as that of the manufacturing enterprise. A numerical example is also presented to demonstrate the application of the proposed approach.     

A game theoretical model for collaborative groups in social applications

In this paper, we address the problem of the free riding behaviour that takes advantage of collaborative educational social groups without contributing back to other participants posts. Free riders are active users who ask questions and draw knowledge from the community but provide very limited or no contributions back to it. Since the survival of a collaborative educational community is highly dependent on its active users and their contributions, motivating free riding users to take an active part would naturally augment the value the community provides and ensure its survivability. As a solution, we formally analyse the impact of the free riding behaviour by means of repeated game theory where classical and generous Tit for Tat are used. Such analysis shows the impact of such behaviour on educational communities and raises the need for other strategies that motivate free riding users to cooperate under the threat of being punished by cooperative ones; hence, we introduce reputation based Tit for Tat strategies. Our study suggests adding reputation as a parameter in users’ profiles in collaborative groups to improve their survivability.     

A multi-agent platform for auction-based allocation of loads in transportation logistics

This paper describes an agent-based platform for the allocation of loads in distributed transportation logistics, developed as a collaboration between CWI, Dutch National Center for Mathematics and Computer Science, Amsterdam and Vos Logistics Organizing, Nijmegen, The Netherlands.The platform follows a real business scenario proposed by Vos, and it involves a set of agents bidding for transportation loads to be distributed from a central depot in the Netherlands to different locations across Germany. The platform supports both human agents (i.e. transportation planners), who can bid through specialized planning and bidding interfaces, as well as automated, software agents. We exemplify how the proposed platform can be used to test both the bidding behaviour of human logistics planners, as well as the performance of automated auction bidding strategies, developed for such settings.The paper first introduces the business problem setting and then describes the architecture and main characteristics of our auction platform. We conclude with a preliminary discussion of our experience from a human bidding experiment, involving Vos planners competing for orders both against each other and against some (simple) automated strategies.     

煤矿井下基于博弈论CR节点协作通信研究

现有无线通信系统在不同矿区通用性不强、通信效果不佳。煤矿井下认知系统可通过对煤矿井下通信环境参数的感知,对感知参数信息的融合、分析,利用动态博弈理论实现动态的频率选择、功率分配、调制方式等参数的调整,获得有效的通信效果和不同矿区兼容。通过Matlab进行了仿真验证,仿真结果表明：该算法能够快速收敛于系统稳定状态,而且,复杂度低,易于实现。     

A service-oriented city portal framework and collaborative development platform

Cities are being equipped with multiple information systems to provide public services for city officials, officers, citizens, and tourists. There have been concerns with efficient service implementation and provision, e.g., data islands and function overlaps between systems and applications. Service-oriented portals are efficient at facilitating information sharing and collaborative work between city systems and users. The goal of this research is to make cities responsive, agile and to provide composite services efficiently and cost efficiently. A service-oriented framework for city portals is proposed to design, integrate and streamline city systems and applications. A model driven collaborative development platform of the proposed framework was developed for service-oriented digital portals. The architecture and implementation issues of the platform are discussed. The service identification policies are discussed within the framework. A case study has been developed and evaluated on the platform to provide a composite service, i.e., a traffic search service on a city portal.     

Multi-agent team cooperation: A game theory approach

The main goal of this work is to design a team of agents that can accomplish consensus over a common value for the agents’ output using cooperative game theory approach. A semi-decentralized optimal control strategy that was recently introduced by the authors is utilized that is based on minimization of individual cost using local information. Cooperative game theory is then used to ensure team cooperation by considering a combination of individual cost as a team cost function. Minimization of this cost function results in a set of Pareto-efficient solutions. Among the Pareto-efficient solutions the Nash-bargaining solution is chosen. The Nash-bargaining solution is obtained by maximizing the product of the difference between the costs achieved through the optimal control strategy and the one obtained through the Pareto-efficient solution. The latter solution results in a lower cost for each agent at the expense of requiring full information set. To avoid this drawback some constraints are added to the structure of the controller that is suggested for the entire team using the linear matrix inequality (LMI) formulation of the minimization problem. Consequently, although the controller is designed to minimize a unique team cost function, it only uses the available information set for each agent. A comparison between the average cost that is obtained by using the above two methods is conducted to illustrate the performance capabilities of our proposed solutions.     

A cooperative multi-agent platform for invention based on patent document analysis and ontology

We propose a cooperative multi-agent platform to support the invention process based on the patent document analysis. It helps industrial knowledge managers to retrieve and analyze existing patent documents and extract structure information from patents with the aid of ontology and natural language processing techniques. It allows the invention process to be carried out through the cooperation and coordination among software agents delegated by the various domain experts in the complex industrial R&D environment. Furthermore, it integrates the patent document analysis with the inventive problem solving method known as TRIZ method that can suggest invention directions based on the heuristics or principles to resolve the contradictions among design objectives and engineering parameters. We chose the patent invention for chemical mechanical polishing (CMP) as our case study. However, the platform and techniques could be extended to most cooperative invention domains.     

A collaborative platform for cognitive decision making in the Knowledge Society

Two key aspects of the Knowledge Society are the interconnection between the actors involved in the decision making processes and the importance of the human factor, particularly the citizen’s continuous learning and education. This paper presents a new module devoted to knowledge extraction and diffusion that has been incorporated into a previously developed decision making tool concerning the Internet and related with the multicriteria selection of a discrete number of alternatives (PRIOR-Web). Quantitative and qualitative procedures using data and text mining methods have been employed in the extraction of knowledge. Graphical visualisation tools have been incorporated in the diffusion stage of the methodological approach suggested when dealing with decision making in the Knowledge Society. The resulting collaborative platform is being used as the methodological support for the cognitive democracy known as e-cognocracy.     

FlowWiki: A wiki based platform for ad hoc collaborative workflows

Traditional workflow management systems provide rich capabilities for designing, executing, and monitoring well-defined collaborative processes. Yet, for many occasions of collaboration, we do not often have sufficient information about who will participate, what activities people will carry out, and how the entire workflow will change. Accordingly, the problem of managing flexible workflows has been receiving increasing attention during the last decade. This paper presents a novel approach by which collaborative workflows can be configured independently as needed by participants and managed in an ad hoc way. Motivated by the emerging paradigm of collective intelligence, the proposed platform, named FlowWiki, provides a set of useful mechanisms to enable dynamic collaborations without requiring prescribed collaboration model. FlowWiki is an extension of conventional wiki system, and it aims for flexibly managing collaborative workflows by allowing on-demand workflow configuration and event-driven interactions.     

A novel method for coevolving PS-optimizing negotiation strategies using improved diversity controlling EDAs

In agent-mediated negotiation systems, the majority of the research focused on finding negotiation strategies for optimizing price only. However, in negotiation systems with time constraints (e.g., resource negotiations for Grid and Cloud computing), it is crucial to optimize either or both price and negotiation speed based on preferences of participants for improving efficiency and increasing utilization. To this end, this work presents the design and implementation of negotiation agents that can optimize both price and negotiation speed (for the given preference settings of these parameters) under a negotiation setting of complete information. Then, to support negotiations with incomplete information, this work deals with the problem of finding effective negotiation strategies of agents by using coevolutionary learning, which results in optimal negotiation outcomes. In the coevolutionary learning method used here, two types of estimation of distribution algorithms (EDAs) such as conventional EDAs (S-EDAs) and novel improved dynamic diversity controlling EDAs (ID²C-EDAs) were adopted for comparative studies. A series of experiments were conducted to evaluate the performance for coevolving effective negotiation strategies using the EDAs. In the experiments, each agent adopts three representative preference criteria: (1) placing more emphasis on optimizing more price, (2) placing equal emphasis on optimizing exact price and speed and (3) placing more emphasis on optimizing more speed. Experimental results demonstrate the effectiveness of the coevolutionary learning adopting ID²C-EDAs because it generally coevolved effective converged negotiation strategies (close to the optimum) while the coevolutionary learning adopting S-EDAs often failed to coevolve such strategies within a reasonable number of generations.     

A game theory framework for ISP streaming traffic management

The overlay/underlay topology mismatch affects the performance of existing P2P platforms that can generate large volumes of unnecessary inter-ISP network traffic. Although recent works have shown the benefits of network awareness P2P solutions, no studies have focused on the investigation of the ISP behavior and their cooperative/non-cooperative attitudes.This paper proposes a game theoretic framework to help the design of techniques promoting the ISP cooperation in P2P streaming platforms and decreasing unnecessary inter-domain streaming traffic.We first analyze some simple scenarios to discuss the existence of Nash equilibria, the Pareto optimality, and a fairness criterion to refine the equilibrium points. Moreover, we apply ideas from Evolutionary Game Theory to design a distributed schemata that the ISPs can use to reach “socially acceptable” equilibrium points in a large ISP population. Furthermore, we develop a discrete event simulation to evaluate the effectiveness of the Evolutionary Game Theory framework.The study presented in the paper shows that the proposed strategies can effectively stimulate ISP cooperation aiming at the minimization of inter-ISP traffic and help to provide reliable P2P streaming service.     

A survey on game theory applications in wireless networks

While the Quality of Service (QoS) offered to users may be enhanced through innovative protocols and new technologies, future trends should take into account the efficiency of resource allocation and network/terminal cooperation as well. Game theory techniques have widely been applied to various engineering design problems in which the action of one component has impact on (and perhaps conflicts with) that of any other component. Therefore, game formulations are used, and a stable solution for the players is obtained through the concept of equilibrium. This survey collects applications of game theory in wireless networking and presents them in a layered perspective, emphasizing on which fields game theory could be effectively applied. To this end, several games are modeled and their key features are exposed.     

A collaborative platform for integrating and optimising Computational Fluid Dynamics analysis requests

A Virtual Integration Platform (VIP) is described which provides support for the integration of Computer-Aided Design (CAD) and Computational Fluid Dynamics (CFD) analysis tools into an environment that supports the use of these tools in a distributed collaborative manner. The VIP has evolved through previous EU research conducted within the VRShips-ROPAX 2000 (VRShips) project and the current version discussed here was developed predominantly within the VIRTUE project but also within the SAFEDOR project. The VIP is described with respect to the support it provides to designers and analysts in co-ordinating and optimising CFD analysis requests. Two case studies are provided that illustrate the application of the VIP within HSVA: the use of a panel code for the evaluation of geometry variations in order to improve propeller efficiency, and the use of a dedicated maritime RANS code (FreSCo) to improve the wake distribution for the VIRTUE tanker. A discussion is included detailing the background, application and results from the use of the VIP within these two case studies as well as how the platform was of benefit during the development and a consideration of how it can benefit HSVA in the future.