支持需求聚合的C2B旅游电子商务自动谈判系统研究

为了更好地撮合旅游服务供需双方的交易活动,将C2B电子商务模式和自动谈判系统相结合,提出一种新的支持需求聚合的C2B旅游电子商务自动谈判系统。引入Agent技术自动聚合大量分散的旅游服务需求,再由C2B电子商务自动谈判系统通过谈判代理Agent和旅游服务企业方的谈判Agent进行自动谈判,撮合旅游服务供需双方交易。阐述系统的总体框架和运行机制;研究需求聚合的策略和方法;基于FIPA规范设计相应的自动谈判协议和自动谈判过程控制算法。基于JADE开发了一套原型系统,验证了相关设计的可行性。     

基于Agent的辩论谈判系统的协议研究

协议是谈判支持系统实现的基本条件之一。依据经典的BDI（信念、愿望、意图）理论和已有的协议,将人类辩论思想融入,给出了协议的基本语言和逻辑框架,提出了相应的状态转换图,对状态转换图中的推理规则进行了详细阐述,从而构建了更加完整的基于Agent的辩论谈判系统协议。最后结合已有的策略和模型,以系统实现的方式对协议的合理性和有效性进行了验证,并指出了下一步研究方向。     

虚拟制造环境下基于多智能体的敏捷调度策略的研究

该文针对虚拟制造环境下生产作业调度,把多智能体系统的分布式结构和层次式结构有机地结合起来,提出基于多Agent的虚拟环境下车间生产敏捷调度的混合层次结构,并着重介绍了Agent之间的基于招投标机制的谈判协议     

多Agent谈判：一种基于模糊逻辑控制的方法

在分析各种Agent谈判模型不足的基础上，首先给出基于黑板模式的谈判Agent体系结构，然后设计了一个通用的谈判Agent建议的综合评价方法。此外，应用标准可加性模型原理设计了谈判Agent的策略模型，从而构建了应用范围广泛的自动化谈判Agent模型。     

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。     

基于Agent的多问题并行遗传谈判模型

Agent谈判增加了电子商务系统的主动性,一个有效的谈判模型是系统实现的关键。分析了已有Agent谈判模型的特点,设计的基于Agent的多问题并行谈判模型解决了已有谈判模型中存在的谈判问题单一、非并行、不考虑对手收益和固定权重等问题。模型中产生谈判方案的算法的自适应性体现在问题权重、遗传参数和收益偏差的动态调整上,给出了问题实数编码和权重调整公式。最后,设计了一个面向三个问题的电子谈判实例,验证了谈判模型的可行性和有效性。     

基于模糊理论的一对多自动谈判协调策略

针对一对多自动谈判参与各方在谈判过程中因为相互等待而效率低下的问题,提出一种能使谈判过程连续化的基于模糊的协调策略,以达到在尽可能少的时间内得到最满意协议的目的。该策略通过协调Agent灵活地创建和撤离新的谈判线程并在谈判过程中不断更新谈判的信念值进而支持连续谈判,满足开放和动态的谈判环境,提高谈判效率。模拟实验表明,该策略能够对谈判效用和时间进行优化,具有有效性和实用性。     

基于辩论的社会性Agent间的谈判模型

通过对Agent间存在的有关社会性的关键元素进行分析,建立了基于辩论的社会性Agent间的谈判模型,并建立了相关的决策函数;然后通过一个存在于多Agent社会中而具有社会性的Agent间的谈判实例,在假设了相关数据的基础上对模型和决策函数进行了举例计算,分析验证了其有效性,并在对相关的谈判原语作出定义的基础上对此谈判实例的辩论对话过程进行了模拟。     

基于多Agent的谈判支持系统研究

为提高谈判效率，简化其操作，并增加谈判的智能辅助机制，将分布式人工智能中的Agent技术引入谈判过程，提出了以多Agent系统代替谈判人与对手协商的谈判支持系统框架，研究了有关的Agent理论与方法，为新一代高效、快捷的商务谈判支持系统研究提供了新的思路。     

基于协同进化遗传算法的多议题谈判

以协同进化遗传算法模拟自动谈判是目前智能计算和多Agent系统等领域研究的新课题。针对现有文献仅模拟单议题谈判的情况,该文提出基于协同进化遗传算法和适应度共享小生境技术的多议题谈判模拟算法,以轮流出价谈判协议为例进行仿真实验。实验结果表明,该算法能在策略种群中形成局部小生境,生成近似Pareto最优的策略集。     

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.     

An Extended Multi-Agent Negotiation Protocol

This article presents a task allocation protocol that is efficient in time and tolerates crash failures in multi-agent systems. The protocol is an extension of the negotiation protocol defined by Smith and Davis [25, 26] for task allocation. Our extension of the Contract Net Protocol (1) enables an agent to manage several negotiation processes in parallel; (2) optimizes the length of the negotiation processes among agents; (3) reduces the contractors' decommitment situations; (4) enables the detection of failures of an agent participating in a negotiation process and prevents a negotiation process with blocked agents.     

A protocol for multi-agent negotiation in a group-choice decision making process

Negotiation is one of the most important features of agent interactions found in multi-agent systems, because it provides the basis for managing the expectations of the individual negotiating agents, and it enables selecting solutions that satisfy all the agents as much as possible. In order for negotiation to take place between two or more agents there is need for a negotiation protocol that defines the rules of the game; consequently, a variety of agent negotiation protocols have been proposed in literature. However, most of them are inappropriate for Group-Choice Decision Making (GCDM) because they do not explicitly exploit tradeoff to achieve social optimality, and their main focus is solving two-agent negotiation problems such as buyer–seller negotiation. In this paper we present an agent negotiation protocol that facilitates the solving of GCDM problems. The protocol is based on a hybrid of analytic and artificial intelligence techniques. The analytic component of the protocol utilizes a Game Theory model of an n-person general-sum game with complete information to determine the agreement options, while the knowledge-based (artificial intelligence) component of the protocol is similar to the strategic negotiation protocol. Moreover, this paper presents a tradeoff algorithm based on Qualitative Reasoning, which the agents employ to determine the ‘amount’ of tradeoff associated with various agreement options. Finally, the paper presents simulation results that illustrate the operational effectiveness of our agent negotiation protocol.     

A BDI Assignment Protocol With New Cooperative-Concession Strategies

This paper addresses the collaborative linear- assignment problem (CLAP) for a class of allocation applications. CLAP entails using agents to seek a concurrent allocation of one different object for every agent, to optimize a linear sum efficiency function as their (soft) social goal. Anchoring in the standard framework of automated negotiation allows an original belief-desire-intention (BDI) negotiation model for CLAP to be conceptually separated into a BDI assignment protocol and an adopted strategy. Facilitated by this conceptual separation, the contributions of this paper are as follows: 1) providing a rigorous analysis of the protocol and demonstrating its salient properties and 2) formulating new strategies using a novel idea of cooperative concession. Four different strategies for a negotiation agent and the arbitration agent provide 16 arbitration-negotiation combinations running with the protocol, and these are empirically assessed for their performance profiles in negotiation speed and solution quality. Important findings, including the stability of the protocol in producing better than good enough global allocations and the strategic influence of cooperative concessions on performance, are examined. The significance and practicality of this paper in relation to existing work are also discussed.     

基于多Agent系统的自动协商机制及通用协商框架

自动协商是多Agent系统实现协作的关键环节。目前,对协商模型的研究大部分是在特定的应用系统中针对具体协商背景进行研究,协商模型的通用性较差。本文分析了多Agent系统协商机制的三个方面:Agent通信语言、通信方式和交互协议。在此基础上,给出了基于多Agent的通用协商框架GNF,该协商框架包括抽象协商过程、协商规则分类和协商协议。最后,给出了一个基于通用协商框架GNF的原型系统——采用Jess规则引擎实现的多Agent的商品交易系统。     

Time-bound negotiation framework for electronic commerce agents

For efficient and informative coordination of agents especially in electronic commerce environment, a time-bound agent negotiation framework is proposed utilizing a time-based commitment scheme. By attaching commitment duration to agent messages, the traditional contract net protocol is extended to a time-bound negotiation framework (TBNF). The proposed negotiation framework has a new message type which allows for parties to agree upon the extension of a commitment duration, and a novel commitment concept in the form of negative commitment. The semantics of the messages with the commitment duration are interpreted, and then the three typical negotiation protocols are formally defined and compared — nothing-guaranteed protocol, acceptance-guaranteed protocol, and finite-time guarantee protocol — which can be incorporated into TBNF. The TBNF should provide a background for efficient and effective electronic commerce negotiation while accommodating each agent's adaptive negotiation strategy.     

基于提议信息保护下的多属性协商协议研究*

综合分析了多属性协商的特点和现有研究所面临的问题,以设计实用性多属性协商机制为目标,分析和规范协商中的智能体的职能、准则及信息表达形式,从而构建了双边同步多属性协商协议。协议策略得出的结果克服了已有研究成果的典型缺陷,并得到了帕累托最优解。协议通过同步提议机制和对提议信息的屏蔽,减少了参与者之间的猜忌,避免了协商者潜在的利益流失,从而提高了协商的效率和保障了交易的公平性。     

电子商务中的自动协商

描述电子商务中基于智能体的自动协商，给出基于智能体的自动协商模型和协商智能体的体系结构，描述了一组构成协商协议的通信原语。通过约束满足机制、协商策略和提议评估算法实现自动协商。并实现了一个供应链管理中买卖自动协商的原型系统。     

An ontology based approach to organize multi-agent assisted supply chain negotiations

Effective supply chain management (SCM) comprises activities involving the demand and supply of resources and services. Negotiation is an essential approach to solve conflicting transaction and scheduling problems among supply chain members. The multi-agent system (MAS) technology has provided the potential of automating supply chain negotiations to alleviate human interactions. Software agents are supposed to perform on behalf of their human owners only when equipped with sophisticated negotiation knowledge. To better organize the negotiation knowledge utilized by agents and facilitate agents’ adaptive negotiation decision making ability, an ontology-based approach is proposed in this paper. Firstly, the multi-agent assisted supply chain negotiation scheme is presented to configure the general design components of the negotiation system, covering the agent intelligence modules, the knowledge organization method and the negotiation protocol. Then, the ontology-based negotiation knowledge organization method is specified. The negotiation knowledge is separated into shared negotiation ontology and private negotiation ontology to ensure both the agent communicative interoperability and the privacy of strategic knowledge. Inference rules are defined on top of the private negotiation ontology to guide agents’ reasoning ability. Through this method, agents’ negotiation behaviors will be more adaptive to various negotiation environments utilizing corresponding negotiation knowledge.     

Behavioral modeling and verification of multi-agent systems for manufacturing control

Simulation is the primary approach to the performance analysis of multi-agent manufacturing systems. In a typical simulation experiment, varying the agent negotiation protocol’s timing parameters can yield incomparable results in performance terms due to behavioral problems such as deadlocks and livelocks. Formal verification can help resolve such problems and therefore plays an important role in the design of agent negotiation protocols. We describe an efficient and scalable approach to formal verification based on an industrial-strength model checking tool and illustrate it with an example.