网络CSCW建组协商中的Meta-协商研究和应用

自动协商的广泛应用激发了CSCW(ComputerSupportedCooperativeWork)建组的新思路.独特的在建组成员间的“Meta 协商”使得建组协商不同于普通的购买协商。从分析“Meta 协商”存在性出发,提出了描述临时组结构的“组对象”概念, 将“群决策”理论中“投票”方法用作组策略的核心思想,实现了决策群体动态变动的Meta 协商机制。在“限制空间”基础上,讨论了协商中解空间和组空间的变化情况,结合网络应用的需要设计出减少因网络拥塞延迟造成建组失败的实现方案。     

CSCW协同建组自动协商模型研究

文章提出了支持协同工作组建立的自动协商模型,定义了agent协商协议、协商算法和协商agent用于产生及评估offer、counter-offer的效益决策函数,分析了算法时间耗用,与现有协商模型和协商建组FITS/CL框架进行对比,验证了该模型在支持用户参加多个协同组、进行多协商方面的优势,解决了组建立中的群体决策问题,对探索自动建组方式进行有益尝试。     

一种自适应的信任协商协议*

在分析现有的信任管理技术和自动信任协商技术的基础上,分别提出了一种支持信任管理的协商策略和一种最优化的信任协商策略,在此基础上设计了一种自适应信任协商协议。该协议可以实现多协议协商,同时融合了信任管理和自动信任协商系统的优点,能够实现安全域内和跨安全域的信任协商功能,具有良好的可扩展性、灵活性和隐私保护。     

一种不依赖于协商策略的信任协商协议

自动信任协商为开放环境中希望进行资源共享或业务协作的陌生双方提供了一种灵活的信任建立方法。然而现有自动信任协商系统之间不具备可互相操作性,首要原因是缺少一个统一的信任协商协议。提出了一种不依赖于协商策略的信任协商协议,将协议消息划分为资源请求、信息披露和终止协商3种类型并定义了消息的格式,阐明了协商过程的3种状态及状态之间的转化关系,同时给出了协议实现算法。分析表明,该协议支持包括多种格式信任证在内的数字断言和不同策略语言描述的访问控制策略的披露,允许在一次协商过程中使用多种协商策略进行协商,以满足不同应用场景的协商需求,因而具有明显的通用性。     

一种基于多样化历史信息的自动信任协商策略

针对自动信任协商的协商效率问题,提出了一种基于多样化历史信息的自动信任协商策略。本策略将历史信息作用于协商过程中,利用策略有向图来完成协商;利用票证来存储历史协商信息,并采用数字签名技术来保证信息的真实性和完整性。根据历史协商信息在产生方式上的不同,提出了信任票证和历史票证,并结合其特点设计了相关的格式以及验证和工作过程。最后进行了实验仿真,结果表明该模型可以提高重复协商的效率。     

用隐藏证书实现访问策略

为解决在信任管理系统中使用隐藏证书的效率问题,借助于策略表达式和结束前缀,给出了一种使用隐藏证书有效实现复杂访问策略的方案,通过构造策略表达式并对其化简减少了加密和解密的次数,通过“结束前缀”方便了信息的还原。实例显示该方案具有较好的可行性和效率。     

使用案例推理的协商策略研究

为解决自动信任协商过程中协商策略的效率问题,提出了一种采用基于案例推理技术的自动信任协商策略。可管理性概念的基础上,设计出可管理的协商策略,优化了协商处理能力。该策略具有较小的网络开销,较高的安全性等特点。实验结果表明该协商策略具有较高的效率。     

多Agent自动协商策略和算法

针对传统协商过程周期长、代价高的问题,提出了三类形式化的曲线簇来描述Agent所采取的协商策略以及一种数学化和计算机程序化的多Agent自动协商算法。这三类策略分别为急躁型、节俭型和折中型。通过实验模拟发现采用所提出的协商策略和算法更符合人类思维的直观。该方法可应用于多种电子商务交易（如B2B和B2C）等活动中。     

基于对手案例学习的多议题协商决策模型

为了解决多Agent系统(MAS)协商双方在信息对称情况下的自动协商问题,提出了一种用基于支持向量机算法的间接学习对手协商态度的协商方法,提出了不完全信息条件下基于案例和对策论的Agent多议题Pareto最优协商模型,通过支持向量机的方法来学习协商轨迹,得到协商对手在每个协商项的态度,然后利用学习得到的对手协商态度,构造了一个协商的决策模型,此模型能同时基于对手的态度和自身的偏好来做出协商决策。最后通过实验验证了该方法的先进性。     

面向分布式证明的信任协商策略语言和方法

现有信任协商语言对复杂的访问控制策略和协商策略以及信任分布式证明方法的支持都不够全面.在RT(role-based trust-management)语言基础上提出一种面向信任分布式证明和协商的策略语言RTP(role-based trust proving),其特点是能够支持信任分布式证明方法,可以定义复杂角色,保护信任证敏感信息并能避免信任证盲目搜索.给出了RTP语言及其推理规则的语法语义描述,介绍了一种基于RTP语言的信任分布式证明协商示例算法.实验结果表明,该算法支持RTP语言的功能,且比传统信任协商方法有很大的性能提升.     

Electronic Markets for Architects—The Architecture of Electronic Markets

In recent years there has been a move towards more cooperation in the construction industry. While the traditional practice is that the architect chooses the trades, provides the construction plan, and tells the trades what to do, a new initiative has been formed to create cooperative construction teams. Here the architect will discuss details of the construction plan with the trades concerned and all parties work cooperatively on the construction project. This means that there will be many coordination tasks and that communication plays a pivotal role. The paper presents a framework for and an implementation of an electronic marketplace to support such cooperative construction teams. It will be argued that there must be a co-design of the business system (i.e. cooperative construction teams) and the IT system (i.e. the marketplace including the search, negotiation, and fulfilment phases) for efficiently supporting small and medium-sized companies participating in cooperative teams and interacting on electronic marketplaces.     

Unanimously acceptable agreements for negotiation teams in unpredictable domains

A negotiation team is a set of agents with common and possibly also conflicting preferences that forms one of the parties of a negotiation. A negotiation team is involved in two decision making processes simultaneously, a negotiation with the opponents, and an intra-team process to decide on the moves to make in the negotiation. This article focuses on negotiation team decision making for circumstances that require unanimity of team decisions. Existing agent-based approaches only guarantee unanimity in teams negotiating in domains exclusively composed of predictable and compatible issues. This article presents a model for negotiation teams that guarantees unanimous team decisions in domains consisting of predictable and compatible, and alsounpredictable issues. Moreover, the article explores the influence of using opponent, and team member models in the proposing strategies that team members use. Experimental results show that the team benefits if team members employ Bayesian learning to model their teammates’ preferences.     

自动信任协商中一种最小信任披露策略

自动信任协商是通过逐渐请求和披露数字证书在两个陌生实体间建立相互信任的方法。当前对自动信任协商协商策略的研究,往往存在很多问题。文章提出了一种基于期望因子的自动信任协商模型,该模型采用MCD策略,通过分析各信任证书的期望因子,当可能的协商存在时,它能披露和请求最小的信任证找到一条成功的协商路径,当协商不可能成功时,尽快的发现并终止它。它能保证在协商的过程中没有不相关的信任证被披露并且不需要暴露双方的访问控制策略,同时通过实验证了明MCD策略是完备的。     

An agent architecture for multi-attribute negotiation using incomplete preference information

A component-based generic agent architecture for multi-attribute (integrative) negotiation is introduced and its application is described in a prototype system for negotiation about cars, developed in cooperation with, among others, Dutch Telecom KPN. The approach can be characterized as cooperative one-to-one multi-criteria negotiation in which the privacy of both parties is protected as much as desired. We model a mechanism in which agents are able to use any amount of incomplete preference information revealed by the negotiation partner in order to improve the efficiency of the reached agreements. Moreover, we show that the outcome of such a negotiation can be further improved by incorporating a “guessing” heuristic, by which an agent uses the history of the opponent’s bids to predict his preferences. Experimental evaluation shows that the combination of these two strategies leads to agreement points close to or on the Pareto-efficient frontier. The main original contribution of this paper is that it shows that it is possible for parties in a cooperative negotiation to reveal only a limited amount of preference information to each other, but still obtain significant joint gains in the outcome.     

一种AGENT任务求解联盟形成策略

Agent联盟是一组平等的、协作的、共同承担任务的Agent的集合．联盟的形成往往需要较大的通信开销和计算工作量．本文提出一种Agent形成联盟的策略，该策略在系统运行的初始阶段，保证任务分配的优化解．而在随后的运行中基于成功合作者集形成Agent联盟．该策略保证在接近任务分配优化解的情况下，有效减少系统中的可能联盟数以及联盟形成过程中的通信开销和计算量，避免联盟形成过程中的盲目性，节省协商时间提高协商效率．     

A Real-Time Negotiation Model and A Multi-Agent Sensor Network Implementation

This paper describes a negotiation model that incorporates real-time issues for autonomous agents. This model consists of two important ideas: a real-time logical negotiation protocol and a case-based negotiation model. The protocol integrates a real-time Belief-Desire-Intention (BDI) model, a temporal logic model, and communicative acts for negotiation. This protocol explicitly defines the logical and temporal relationships of different knowledge states, facilitating real-time designs such as multi-threaded processing, state profiling and updating, and a set of real-time enabling functional predicates in our implementation. To further support the protocol, we use a case-based reasoning model for negotiation strategy selection. An agent learns from its past experience by deriving a negotiation strategy from the most similar and useful case to its current situation. Guided by the strategy, the agent negotiates with its partners using an argumentation-based negotiation protocol. The model is time and situation aware such that each agent changes its negotiation behavior according to the progress and status of the ongoing negotiation and its current agent profile. We apply the negotiation model to a resource allocation problem and obtain promising results.     

Collaboration and underlying issues or the surprises of cooperative dialogues

The observation of cooperative dialogues between production and maintenance workers of a dairy has revealed that socio-organisational factors had strong effects on cooperation. In order to better understand the nature of these factors, the sociological literature on autonomy, rule generation, negotiation and conflict is reviewed. A methodology based on inferential pragmatics is developed in order to analyze what takes place socially in operational exchanges and makes it possible to identify rules for cooperative functioning that are specific to this work situation, and that relate to the defence of the territory of each individual. The conclusion stresses that cooperative dialogues are also the place where social stakes are adjusted and discusses potential applications of the proposed framework to the design of cooperative systems.     

A Reluctance-Based Cost Distribution Strategy for Multiagent Planning

In this paper we present CODMAPS, a COst Distribution Method for Agent Planning Systems. The strategy is based on individual distribution of cost and competitive behavior.Our model emulates how human agents work in expert groups. They all share a common objective, however, they also have individual interests and try to steer the planning process towards their own goals. Two opposing trends coexist within the set: global co-operation and individual utility maximization. External evaluation must guarantee the validity of the final plan at global level, but a negotiation and cost distribution strategy must ensure that cost is adequately shared throughout the agent set. We introduce the concept of reluctance as a regulation mechanism to facilitate it. A statistical model allows agents to adapt their attitude towards negotiation depending on their negotiation state vector , which encompasses all history of previous negotiations by the agent.Previous research into this problem had taken the rational approach. A group of agents choose the best alternative given the current possibilities. This not only forces the agents to exchange and understand other agents' proposals (which is computationally expensive), but also neglects the past negotiation history of each individual agent.Our approach facilitates distribution of cost across the agent set given the agents' past history and the importance of their constraints. The more taxed an agent becomes the more reluctant it will be to relax, thus pushing other agents less taxed to accept to compromise. It does not need explicit constraint information exchange, thus simplifying the negotiation process.