Agent based automated trust negotiation model

To enhance the practicability of the trust negotiation system, an agent based automated trust negotiation model （ABAM） is proposed. The ABAM introduces an agent to keep the negotiation process with no human intervention. Meanwhile, the ABAM specifies the format of a meta access control policy, and adopts credentials with flexible format to meet the requirements of access control policies instead of disclosing the whole contents of a certificate. Furthermore, the ABAM uses asymmetric functions with a high security intensity to encrypt the transmitting message, which can prevent information from being attacked. Finally, the ABAM presents a new negotiation protocol to guide the negotiation process. A use case is studied to illuminate that the ABAM is sound and reasonable. Compared with the existing work, the intelligence, privacy and negotiation efficiency are improved in the ABAM.

Issues in automated negotiation:protocol and ontology

In the environment of e-commerce, agents in automated negotiation should share common concept of what they are bargaining and a rule of how to bargain. State of the art overviews of automated negotiation is given. The main barriers to automated negotiation such as protocol and ontology are discussed. Then, a model of automated negotiation is presented with the ontologies of roles and goods described by web ontology language （OWL）, the proposal strategies based on the information sets, and a set of rules for agent interaction. In this model, agents coming from different organizations can negotiate automatically based on common ontologies defined by OWL and formal protocol. This makes it possible for the automated negotiation to be performed in an open environment such as Internet, not merely in a closed system.

New E-Commerce Model Based on Multi-Agent Automated Negotiation

A new multi-agent automated negotiation model is developed and evaluated, in which two competitive agents, such as the buyer and seller, have firm deadlines and incomplete information about each other. The negotiation is multi-dimensional in different cases. The model is discussed in 6 kinds of cases with different price strategies, warrantee strategies and time strategies. The model improves the model of Wooldridge and that of Sycara to a certain extent. In all possible situations, the optimal negotiation strategy is analyzed and presented, and an e-commerce model based on multi-agent automated negotiation model is also illustrated for the e-commerce application in the future.

Automated Negotiation in E Commerce: Protocol Relevance and Improvement Techniques

We all negotiate,formally or informally,in jobs,in day today lives and outcomes of negotiations affect those processes of life.Although negotiation is an intrinsic nature of human psyche,it is very complex phenomenon to implement using computing and internet for the various purposes in E Commerce.Automation of negotiation process poses unique challenges for computer scientists and researchers,so here we study how negotiation can be modeled and analyzed mathematically,what can be different techniques and strategies or set of rules/protocols to be implemented and how they can be relevantly implemented.We are in a quest to find out how this complex process,which involves human psyche can be automated using computers and modern day technologies.Now,the quest is not only automation,looking at the research in the related field in last ten years;but it is all about finding solutions to make e-negotiation more efficient and more accurate,as well as useful in any kind of electronic trading situations.Here is an attempt to consolidate our work of last few years on automation of negotiation process;we call it as negotiation protocol on research,study as well as implementation level of negotiation automation.Overall,we are trying to give few solutions to make the automation more efficient.

Agent Modeling of User Preferences Based on Fuzzy Classified ANNs in Automated Negotiation

In agent-based automated negotiation research area,a key problem is how to make software agent more adaptable to represent user preferences or suggestions,so that agent can take further proposals that reflect user requirements to implement ecommerce activities like automated transactions.The difficulty lies in the uncertainty of user preferences that include uncertain description and contents,non-linear and dynamic variability.In this paper,fuzzy language was used to describe the uncertainty and combine with multiple classified artificial neural networks(ANNs) for self-adaptive learning of user preferences.The refinement learning results of various negotiation contracts' satisfaction degrees in the extent of fuzzy classification can be achieved.Compared to unclassified computation,the experimental results illustrate that the learning ability and effectiveness of agents have been improved.

An Automated Negotiation Protocol Based On Game Theory

With the goal of meeting one-to-many negotiation mechanism in the process of inter-basin water transfer, according to features of all interest subjects in analysis of inter-basin water transfer, a one-to-many synchronous bidding negotiation model based on bidding rules of game theory is structured, which analyzes and negotiates the functions, code of conduct and information expression of each subject. In order to optimize overall interests and individual interests, and a series of parameters in the negotiation, the paper propose various rules corresponding to the negotiation model so that the efficiency of each interest subject and fair distribution of negotiation proceeds can be safeguarded in the inter-basin water transfer system.

Automatic Negotiation with Profiles and Clustering of Agents

This paper presents a model of automatic negotiation agents in an open environment. Agents are motivated by the gain they may obtain while fulfilling their goals, but their behaviour can change during negotiation according to previous interactions with other agents in the system. Changing behaviour may refer to either the use of different negotiation strategies or to concessions made for other agents, with which they have successfully negotiated in the past. To this aim, an agent develops a set of partners’ profiles during negotiation: the preference profile, the cooperation profile, and the group negotiation profile. The first two profiles characterize individuals, while in a group negotiation profile, several agent profiles are clustered according to commonly discovered features. Different approaches to the development of these profiles are presented.

Negotiation Model for Shopping Agents in E-marketplace

Automated negotiation is the key techniques for reaching agreements in agent-mediated electronic commerce. Current automated negotiation models assume that users know the value of the product or service they want to buy and provide their agents with a reservation price, and the agents make offers and reach agreements with other agents according to this reservation price. However, in real world electronic marketplaces users probably do not know the exact value of the item, which is in terms of price, and the reservation price they set to their agents only means the maximum price they are willing to pay for the item. In this paper, we propose a negotiation model to deal with the valuation problem. The shopping agent in our model can deliberate the market price and the seller agent’s reservation price from public available information and the seller agent’s proposals. Also in order to conform with the real world negotiation conditions, we introduce negotiation features of real world human shopping such as multiple sellers, valuation, ultimatum, and learning from available information, etc. into our model.

Service Parameter Exposure and Dynamic Service Negotiation in SDN Environments

Software-defined networking （SDN） is a generic term and one of the major interests of the telecoms industry （and beyond） over the past two years. However, defining SDN is a somewhat controversial exercise. The claimed flexibility, as well as other presumed assets of SDN, should be carefully investigated. In particular, the use of SDN to dynamically provision network services suggests the introduction of a certain level of automation in the overall network service delivery process, from service parameter negotiation to delivery and operation. This paper aims to clarify the SDN landscape and focuses on two main aspects of the SDN framework： net- work abstraction, and dynamic parameter exposure and negotiation.

Integrating Interaction Framework for Agent Negotiation

Agent negotiation has become increasingly important since the advent of electronic commerce.There are two kinds of interactions in the process of agent negotiation.One is the interaction between different agents,and the other is the interaction between the agent and the human user.In this paper,firstly,we introduce Q language,a scenario description language for designing interactions between agents and human users.Then we propose an integrating interaction framework for agent negotiation,in which both kinds of interactions are described by Q scenario.Our framework can make the interaction process open and easy to be understood by the users.Users can understand how the negotiation process goes and what is happening in the system including some erroneous or inappropriate actions caused by the negotiation agent.This gives the users a chance to terminate or change the behavior of negotiation agent in time to avoid unfavorable negotiation outcome.In addition,users can customize the agent's behaviors through visible interactions with it.

An E-Negotiation Agent Using Rule Based and Case Based Approaches: A Comparative Study with Bilateral E-Negotiation with Prediction

The research in the area of automated negotiation systems is going on in many universities. This research is mainly focused on making a practically feasible, faster and reliable E-negotiation system. The ongoing work in this area is happening in the laboratories of the universities mainly for training and research purpose. There are number of negotiation systems such as Henry, Kasbaah, Bazaar, Auction Bot, Inspire, and Magnet. Our research is based on making an agent software for E-negotiation which will give faster results and also is secure and flexible. The negotiation partners and contents between the service providers change frequently. The negotiation process can be transformed into rules and cases. Using these features, a new automated negotiation model for agent integrating rule based and case based reasoning can be derived. We propose an E-negotiation system, in which all product information and multiple agent details are stored on the cloud. An E-negotiation agent acts as a negotiator. Agent has user’s details and their requirements for a particular product. It will check rules based data whether any rule is matching with the user requirement. An agent will see case based data to check any similar negotiation case matching to the user requirement. If a case matches with user requirement, then agent will start the negotiation process using case based data. If any rule related requirement is found in the rule base data, then agent will start the negotiation process using rule based data. If both rules based data and cases based data are not matching with the user requirement, then agent will start the negotiation process using Bilateral Negotiation model. After completing negotiation process, agent gives feedback to the user about whether negotiation is successful or not. The product details, rule based data, and case based data will be stored on the cloud. So that system automatically becomes flexible. We also compare E-negotiation agent automated negotiation and behavior prediction system to prove that using rule based and case based approaches system should become fast.

Resolving conflicts between negotiation success and sensitive information protection in automated trust negotiation

Automated trust negotiation （ATN） is an approach to establishing mutual trust between strangers wishing to share resources or conduct business by gradually requesting and disclosing digitally signed credentials. In ATN, there are conflicts between negotiation success and sensitive information protection, that is, these two needs cannot be given priority at the same time, which is a challenging problem to resolve. In this paper, a language independent ATN framework, which is dynamic, flexible and adaptive, is presented to address this problem, ensuring negotiation success without sensitive information leakage. This framework is independent of the policy language which is used. However, the language used should have the capability to specify all kinds of sensitive information appearing in credentials and policies, and support the separation of attribute disclosure from credential disclosure. Thus definitions of new language features, which can be incorporated into existing policy languages, are given, enabling the used language to support the capabilities mentioned above.

Designing Negotiating Agent for Automated Negotiations

Traditional research in automated negotiation is focused on negotiation protocol and strategy.This paper studies automated negotiation from a new point of view, proposes a novel concept, namely negotiating agent, and discusses its significance in construction of automated negotiation system, with an abstract model formally described and the architecture designed, which supports both goal-directed reasoning and reactive response. A communication model was proposed to construct interaction mechanism used by negotiating agents, in which the negotiation language used by agents is defined.The communication model and the language are defined in a way general enough to support a wide variety of market mechanisms, thus being particularly suitable for flexible applications such as electronic business. The design and expression of the negotiation ontology is also discussed. On the base of the theoretical model of negotiating agent, negotiating agent architecture and negotiating agent communication model (NACM) are explicit and formal specifications for the agents negotiating in an E-business environment; especially, NACM defines the negotiation language template shared among all agents formally and explicitly. The novelty of the communication model is twofold.

基于TD3算法的自动协商策略

协商是人们就某些议题进行交流寻求一致协议的过程.而自动协商旨在通过协商智能体的使用降低协商成本、提高协商效率并且优化协商结果.近年来深度强化学习技术开始被运用于自动协商领域并取得了良好的效果,然而依然存在智能体训练时间较长、特定协商领域依赖、协商信息利用不充分等问题.为此,本文提出了一种基于TD3深度强化学习算法的协商策略,通过预训练降低训练过程的探索成本,通过优化状态和动作定义提高协商策略的鲁棒性从而适应不同的协商场景,通过多头语义神经网络和对手偏好预测模块充分利用协商的交互信息.实验结果表明,该策略在不同协商环境下都可以很好地完成协商任务.

基于机器学习的自动协商决策模型

所提出的模型利用协商历史中隐含的信息自动对数据进行标注以形成训练样本,用最小二乘支持向量回归机学习此样本得到对手效用函数的估计,然后结合自己和对手的效用函数构成一个约束优化问题,用遗传算法求解此优化问题,得到的最优解就是己方的反建议.实验结果表明,在信息保密和没有先验知识的条件下,此模型仍然表现出较高的效率和效用.

自动信任协商及其发展趋势

属性证书交换是一种在不同安全域里共享资源或进行商业事务交易的陌生人之间建立双方信任关系的重要手段.自动信任协商则通过使用访问控制策略提供了一种方法来规范敏感证书的交换,从而保护了用户的敏感证书信息、敏感访问控制策略与个人隐私,以及提高协商效率和协商成功率.对自动信任协商的研究动态进行了调研,对该领域的相关技术进行了归类及介绍.在认真分析现有技术的基础上,总结了当前自动信任协商的不足,并指出了自动信任协商继续发展应遵守的原则以及自动信任协商的未来发展趋势.

基于Agent的谈判模型研究

提出了一种基于Agent技术的谈判模型,应用模糊数学理论建立了谈判论据及谈判解接受度数学模型。采用约束放松的方法对谈判模型进行求解,得到了谈判Agent满意的谈判解。阐述了双边多属性谈判过程,设计并开发了Agent谈判系统原型,实例计算分析表明,该谈判模型是一种双赢的谈判模型。

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。

可信计算中远程自动匿名证明的研究

远程证明是可信计算的一个重要特征,目的是证明远程平台的身份或配置信息是否可信.常用的二进制证明方法不仅暴露了本地平台的配置信息,而且在现实情况中很难处理平台多样性问题.文中提出的可信计算中远程自动匿名证明方案利用环签名实现直接匿名证明,隐藏了平台的身份信息,以属性证书代替平台配置信息,可以有效防止私有信息的暴露,同时兼顾到对系统的升级和备份的可信评测.证明协议避免了使用零知识证明.分析结果显示,具有较高的实现效率.

基于人工蜂群算法的电子商务多Agent自动谈判模型

由于现有电子商务自动谈判模型在不断动态变化的网络环境中匹配慢、整体效用值低,结合人工蜂群算法的原理及求解流程,给出一种电子商务自动谈判模型。该模型基于多Agent多属性的自动谈判模式,融合符合实际的商务谈判方式,着重将电子商务自动谈判的Agent匹配与人工蜂群算法求解的过程相结合,以快速准确获得使整体利益最大的解。通过求解一个电子采购实例并与其他算法的求解效率进行对比,验证了该模型的有效性。