Technical framework for Internetware: An architecture centric approach

Being a new software paradigm evolved by the Internet, Internetware brings many challenges to the traditional software methods and techniques. Sponsored by the national basic research program （973）, researchers in China have developed an architecture centric technical framework for the definition, incarnation and engineering of Internetware. First of all, a software model for Internetware is defined for what to be, including that Internetware entities should be packaged as components, behaving as agents, interoperating as services, collaborating in a structured and on demand manner, etc. Secondly, a middleware for Internetware is designed and implemented for how to be, including that Internetware entities are incarnated by runtime containers, structured collaborations are enabled by runtime software architecture, Internetware can be managed in a reflective and autonomic manner, etc. Thirdly, an engineering methodology for Internetware is proposed for how to do, including the way to develop Internetware entities and their collaborations by transforming and refining a set of software architectures which cover all the phases of software lifecycle, the way to identify and organize the disordered software assets by domain modeling, etc.     

基于模糊评判的Agent联盟效用分配

多个Agent同时形成任务求解联盟时,联盟效用的分配是一个棘手的问题。已有的平均分配和基于能力大小的分配策略都没有反映出Agent对联盟贡献的差异性,不利于联盟的形成和完成任务的绩效。提出了一种基于模糊评判的联盟效用分配方法。首先模糊评价Agent的各维能力贡献率,然后综合计算出整体贡献因子,并据此完成联盟效用的合理分配,最后通过实例分析说明了此方法的有效性。     

Software Evolution for Moving into and Moving within Internetware Paradigm

Internetware has been an emerging software paradigm to best support computing in the Internet era. Internetware emphasises accommodating the open, dynamic and uncontrollable natures of Internet, which directly and indirectly relates software evolvability. This paper observes that evolving non-Internetware software into the Internetware paradigm and evolving software within Internetware will be two main research and practical issues, and hence proposes an integrated approach to address these two issues. The proposed framework is based a three-dimension structure, with System Functions, System Quality and System models as dimensions. With this framework, evolving software into internetware paradigm can be viewed mainly as changing the qualities of existing software and evolving software within Internetware paradigm can be viewed mainly as changing software functions. The involved prototype tool, working examples and experiments conducted, are used to illustrate the proposed approach.     

基于文化算法的多agent 联盟在网络舆情监测中的应用

对网络舆情监测监控云平台上集聚的海量技术agent, 如果只是逐一agent 搜寻使联盟的利益最大化, 将耗费大量的时间和费用. 为解决该问题, 提出了基于“能力群”的动态联盟机制, 通过动态增加或删除“能力群”中的agent 来增加联盟完成复杂任务的能力; 并提出一种基于文化算法的“能力群”agent 联盟算法, 详细讨论了算法的流程、编码、选择、交叉和变异操作的规则, 以及基于“能力群”特征的交叉算法. 仿真结果表明, 所提出的算法是可行和有效的.

     

Agent long-term coalition credit

Agent trust researches become more and more important because they will ensure good interactions among the software agents in large-scale open systems. Moreover, individual agents often interact with long-term coalitions such as some E-commerce web sites. So the agents should choose a coalition based on utility and trust. Unfortunately, few studies have been done on agent coalition credit and there is a need to do it in detail. To this end, a long-term coalition credit model (LCCM) is presented. Furthermore, the relationship between coalition credit and coalition payoff is also attended. LCCM consists of internal trust based on agent direct interactions and external reputation based on agent direct observation. Generalization of LCCM can be demonstrated through experiments applied in both cooperative and competitive domain environment. Experimental results show that LCCM is capable of coalition credit computation efficiently and can properly reflect various factors effect on coalition credit. Another important advantage that is a useful and basic property of credit is that LCCM can effectively filter inaccurate or lying information among interactions.     

Fuzzy Constraint-Based Agent Negotiation

Conflicts between two or more parties arise for various reasons and perspectives. Thus, resolution of conflicts frequently relies on some form of negotiation. This paper presents a general problem-solving framework for modeling multi-issue multilateral negotiation using fuzzy constraints. Agent negotiation is formulated as a distributed fuzzy constraint satisfaction problem (DPCSP). Fuzzy constrains are thus used to naturally represent each agent's desires involving imprecision and human conceptualization, particularly when lexical imprecision and subjective matters are concerned. On the other hand, based on fuzzy constraint-based problem-solving, our approach enables an agent not only to systematically relax fuzzy constraints to generate a proposal, but also to employ fuzzy similarity to select the alternative that is subject to its acceptability by the opponents. This task of problem-solving is to reach an agreement that benefits all agents with a high satisfaction degree of fuzzy constraints, and move towards the deal more quickly since their search focuses only on the feasible solution space. An application to multilateral negotiation of a travel planning is provided to demonstrate the usefulness and effectiveness of our framework.     

基于熟人的Agent联盟策略

在多ａｇｅｎｔ系统中,ａｇｅｎｔ可以通过协商形成联盟来完成任务求解。本文基于ａｇｅｎｔ联盟的统计规律提出了ａｇｅｎｔ熟人的概念,以熟人为基础的联盟策略可以有效减少联盟形成过程中的通讯开销和计算量。随后给出了一种基于该策略的联盟竞争任务的算法,该算法适用于动态,开放的环境、无中心控制,不存在通讯和计算瓶颈。     

Interfacing Indigolog and OAA: A Toolkit for Advanced Multiagent Applications

In this paper, we describe an interface library IG-OAAlib that supports the development of Open Agent Architecture (OAA) agents using the INDIGOLOG agent programming language. OAA is a multi-agent infrastructure that supports facilitated communication. INDIGOLOG is a high-level agent programming language based on logic that supports planning and allows complex agent behaviors to be specified. Full-fledged INDIGOLOG agents written using our interface library can be both reactive and proactive, thus overcoming one of the limitations of PROLOG-based agents in the OAA framework. The interface hides all of the low-level procedures that are used to communicate with the OAA system, as well as OAA initialization, thereby leaving the INDIGOLOG programmer free to concentrate on the functionality of the agent. A multi-robot mail delivery application developed using the library is presented.     

Internal structure of coalitions in competitive and altruistic graphical coalitional games

This paper introduces a certain graphical coalitional game where the internal topology of the coalition depends on a prescribed communication graph structure among the agents. The game Value Function is required to satisfy four Axioms of Value. These axioms make it possible to provide a refined study of coalition structures on graphs by defining a formal graphical game and by assigning a Positional Advantage, based on the Shapley value, to each agent in a coalition based on its connectivity properties within the graph. Using the Axioms of Value the graphical coalitional game can be shown to satisfy properties such as convexity, fairness, cohesiveness, and full cooperativeness. Three measures of the contributions of agents to a coalition are introduced: marginal contribution, competitive contribution, and altruistic contribution. The mathematical framework given here is used to establish results regarding the dependence of these three types of contributions on the graph topology, and changes in these contributions due to changes in graph topology. Based on these different contributions, three online sequential decision games are defined on top of the graphical coalitional game, and the stable graphs under each of these sequential decision games are studied. It is shown that the stable graphs under the objective of maximizing the marginal contribution are any connected graph. The stable graphs under the objective of maximizing the competitive contribution are the complete graph. The stable graphs under the objective of maximizing the altruistic contribution are any tree.     

Agent Reasoning Mechanism for Long–Term Coalitions Based on Decision Making and Trust

We address long–term coalitions that are formed of both customer and vendor agents. We present a coalition formation mechanism designed at the agent level as a decision problem. The proposed mechanism is analyzed at both system and agent levels. Our results show that the coalition formation mechanism is beneficial for both the system—it reaches an equilibrium state—and for the agents—their gains highly increase over time.     

面向动态任务合作求解的联盟模型

多Agent系统中,Agent间通过形成联盟达到提高任务求解能力,获取更多收益的目的。主要关注联盟模型的改进和联盟形成阶段的改进,基于ARG(agent,role,group)元模型和学习机制提出了一种采用角色和学习机制的新联盟模型CLAR(coalition model based on learnin gagent and role);在采用合同网协议的CLAR联盟模型中提出了两阶段联盟形成机制;通过捕食者问题实验验证了角色和学习机制的作用,以及两阶段联盟形成机制在减少通讯代价上的作用。     

一种基于按劳分配原则的联盟形成策略

联盟形成主要研究如何在联盟内Agent间划分联盟效用,使Agent在决策时愿意形成更优的联盟。但是已有的联盟形成策略对额外效用的平均分配没有考虑到每个Agent对联盟的贡献大小以及加入后的利益,不利于联盟的形成。提出一种基于按劳分配原则的联盟形成策略,该策略运用按能力分配原则对额外效用进行合理分配,体现了“能者多劳,多劳多得”的特点,维护了个体间的利益,优于Shapley值方法和平均分配法,较好地满足了联盟的稳定性和时效性等要求。     

一种新的动态Agent联盟形成机制

动态Agent联盟的形成机制是当前MAS研究的一个重要方向.为了克服目前Agent联盟形成机制存在的Agent利用率不高等缺陷,本文提出了一种基于"二次招/投标"和NOAH规划的动态Agent联盟形成机制.该机制采用"二次招/投标"法形成动态联盟,采用NOAH规划进行任务规划和分解,能够在满足子任务时间约束的条件下,充分发挥Agent的并行执行能力;并使得Agent能够动态加入和退出联盟,从而提高了Agent的利用率,保证了自利Agent自身利益的最大化.最后通过一个典型的实例验证了其有效性.     

Emotions in autonomous agents: comparative analysis of mechanisms and functions

Emotion mechanisms are often used in artificial agents as a method of improving action selection. Comparisons between agents are difficult due to a lack of unity between the theories of emotion, tasks of agents and types of action selection utilised. A set of architectural qualities is proposed as a basis for making comparisons between agents. An analysis of existing agent architectures that include an emotion mechanism can help to triangulate design possibilities within the space outlined by these qualities. With this in mind, twelve autonomous agents incorporating an emotion mechanism into action selection are selected for analysis. Each agent is dissected using these architectural qualities (the agent architecture, the action selection mechanism, the emotion mechanism and emotion state representation, along with the emotion model it is based on). This helps to place the agents within an architectural space, highlights contrasting methods of implementing similar theoretical components, and suggests which architectural aspects are important to performance of tasks. An initial framework is introduced, consisting of a series of recommendations for designing emotion mechanisms within artificial agents, based on correlations between emotion roles performed and the aspects of emotion mechanisms used to perform those roles. The conclusion discusses how problems with this type of research can be resolved and to what extent development of a framework can aid future research.     

网构软件数据语用的一种动态支撑方法

网构软件不确定的数据需求导致了其数据语用(data pragmatics,简称DP)的不确定性,进而要求数据语用的支撑机制具备动态适应能力,即应用的对象属性与数据表之间的对应关系可以按需动态地创建、更新、删除.针对当前持久化技术缺乏数据语用的动态适应性问题,提出了一种基于对象/关系映射的数据语用动态支撑方法POD(persistence on demand),并且在主流ORM(object/relational mapping)框架的基础上实现了一个遵循POD的持久化框架的原型系统.     

一种情境驱动的网构软件体系架构与支撑环境

本文从网构软件Internet环境下涉及的各类事物和事件情境及情境的整个生命周期出发,以情境驱动为核心,对网构软件的体系结构与支撑环境展开研究,以支持服务实体的自适应、自演化行为。本文研究了Internet环境下服务实体交互与协同关系中的各种情境构成,给出了一个适合网构软件的情境本体定义。在此基础上,给出了一种基于情境感知的网构软件体系架构,并描述了在这一架构下网构软件按需聚合和动态演化的模型与机制。围绕该应用场景,结合服务实体实际运行时的特点及要素,给出了该体系架构下网构软件的支撑环境软件设计。最后,本文给出了一种基于OSGi服务平台的支撑环境参考实现。     

用遗传算法实现多智能体联盟的形成

在多Agent系统中，当单个Agent不能或不能有效完成特定的任务时，任务就必需分配给一组Agent，即Agent将形成联盟。本文将讨论Agent联盟的形成，并将遗传算法应用于Agent联盟形成中，希望可以快速、高效地找出合适的Agent联盟。     

一种面向网构软件体系结构的信任驱动服务选取机制

基于信任度评估的思想,从软件服务选取的角度对此问题进行了探讨,提出一种面向网构软件体系结构的信任驱动的服务选取机制:首先,给出一种通用的、机器可理解的应用需求及信任演化策略描述规范;其次,采用一种基于反馈的信任形成及决策机制,并给出一个信任驱动的服务选取算法;最后,给出一种面向网构软件体系结构的信任驱动的服务选取支撑框架.初步实践表明,上述机制为开发可信网构软件提供了有效支持.