自主移动机器人混合式体系结构的设计与实现

针对以往自主移动机器人体系结构在实时处理方面的不足，提出了一种基于多智能体的混合式体系结构，统一规划了机器人系统的软硬件结构，在该体系结构中设计并实现了协调Agent和推理Agent两种智能体，针对紧急事件进行了更实时的Agent实现，有效的提高的自主移动机器人在突发事件时的实时性，提出了使用多样化的信息组织形式，增强了系统的自适应能力和易扩展性。本文的实验结果表明在紧急状态下，系统的反应时间有效缩短，增加了系统的智能性和实时性。     

基于Jave的Agent研究

通过研究Agent开发平台的体系结构与Agent内部体系结构—BDI模型的实现机制，研究一个基于Java语言扩展与BDI概念模型的Agent开发平台JBSAD。为Agent系统的开发提出了一种方法，方便了Agent应用系统的开发。     

基于HLA的多Agent系统体系结构研究

本文在分析了目前AI领域对多Agnet系统体系结构研究成果的基础上，结合HLA／RTI仿真技术框架在高层体系结构上的应用前景，提出了一种基于HLA的多Agent系统体系结构，在这个框架下，实现了一个Agent对象模型，介绍了如何利用Agnet通信语言KQML进行互操作的过程，详述了多Agent系统的工作原理，最后指出了多Agent系统在复杂系统开发中的应用前景。     

基于多Agent技术的油田智能防汛系统

本文分析了基于多Agent的决策调度在防汛系统中应用的可行性，给出了多Agent防汛决策调度系统的设计方案和软硬件体系结构．通过在油田防汛决策支持系统中的应用，说明多Agent的体系结构降低了复杂任务的协作难度，实现了分布式智能处理，提高了决策调度的能力。     

基于Agent的自主式智能机器人体系结构及集成系统

自主式智能机器人体系结构的关键是寻求精确推理和快速反应之间的最佳折衷,分布式多Agent系统为体系结构的实现提供了新的途径.本文提出基于多Agent的面向任务集成的自组织体系结构IRASO,详细讨论该结构的计算机系统集成方案,介绍基于异质分布式计算的网络集成环境Robix,并通过仿真分析该系统的特性.     

MAS Builder：一种基于计划的多Agent系统开发平台

多Agent系统便于建模和实现复杂、庞大的应用系统，是一种新的软件开发范型。本文简要介绍了一种基于计划的通用多Agent系统开发平台-MAS Builder，并对其体系结构、基于计划的多Agent合作和任务管理等问题进行了较为详细的阐述。     

基于多Agent的人工鱼群自组织行为算法

在基于认知的人工鱼行为模型的基础上，增加实现鱼群个体间通信及鱼群与环境交互的互操作行为模块，建立面向群体行为的人工鱼体系结构与模型。提出了一种基于多Agent的人工鱼群自组织行为的研究方法：将基于这种体系结构的人工鱼作为Agent，其能感知环境信息，产生意图，规划行为。建立鱼群中Agent的运动、捕食、逃逸模型，通过个体间的相互作用涌现出群体的自组织行为，从而实现对鱼群的逼真模拟。     

基于多Agent的开放信息集成体系结构实现方法研究

为了提高多Agent系统和基于多Agent的开放信息集成体系结构的实用性,文章首先分析了Agent的特性与软件组件模型的关系,软件组件模型是关于开发可重用软件组件和组件之间相互通信的一组标准,是实现分布对象之间的互操作的基础之一。然后,研究了以软件组件模型为基础实现Agent和多Agent系统的方法,并探讨了在现有主流开发工具平台上实现基于多Agent的开放信息集成体系结构的方法。最后,给出了一个应用实例。     

一种基于软件Agent的分布式网络管理体系结构

提出了一种基于软件Agent的分布式网络管理体系结构DANMA（Distributed software Agent-based Network Management Architecture)。整个体系结构分为接口Agent、管理服务Agent和设备Agent三个层面。并对管理服务的提供与定制、自动 管理和管理系统集成三个问题进行了讨论。这种体系结构将网络管理的智能和控制分布到整个网络之中，使得整个管理系统具有自适应、自组织的特性、与传统集中式管理系统相比，此种结构的系统更易于集成，易于扩充，并提高了管理服务的复用性。     

Agent技术在Web数据仓库结构中的应用研究

针对基于Web的数据仓库体系结构存在的问题,在该体系结构中引入软件Agent技术,运用移动Agent技术来解决传统方法难以解决的一些主要问题,提出了一种基于Agent的Web数据仓库系统体系结构。文中发挥数据仓库技术和Web技术结合的优势,重点研究了Agent技术在Web服务器端的应用,在把有用的Web数据集成并入到数据仓库中这一目前的研究热点问题中,提出了基于Agent技术将HTML页面转化为XML数据源的解决方案。此外,文章分别研究了应用服务器端和数据仓库系统中的Agent技术的应用,并提出了将Agent技术引入后实现基于Web的数据仓库体系的关键技术。     

基于Agent的用户偏好决策模型及其应用

智能体及其组成的智能体系统是人们解决用传统方法难以解决的复杂问题的一个新途径,以复杂适应系统、智能体系统等理论为指导,吸取了智能体强化学习的基本原理,提出了一种基于智能体的用户偏好决策模型,并将其成功应用在互联网搜索中,不仅提高了搜索的质量,同时具有一定的创新性。     

基于自适应共生进化的自主体快速强化学习研究

文章研究了一类基于自适应共生进化模型的自主体构造方法,提出了基于自适应共生进化算法（ＡＳＥ）的一种进化强化学习方法,该方法不仅可以高效地进行神经网络决策系统的设计,而且在多自主体组成的自律系统的群体行为进化中可快速学习而收敛,并且通过多样度调节维持了群体多样性,克服了未成熟收敛现象。研究者将该方法用于人工生物中求偶通讯规范的研究,通过在环境中的生存和行为学习,雌雄个体都可有效地学习到成功的求偶通讯规范。     

一种基于强化学习的学习Agent

强化学习通过感知环境状态和从环境中获得不确定奖赏值来学习动态系统的最优行为策略,是构造智能Agent的核心技术之一,在面向Agent的开发环境AODE中扩充BDI模型,引入策略和能力心智成分,采用强化学习技术实现策略构造函数,从而提出一种基于强化学习技术的学习Agent,研究AODE中自适应Agent物结构和运行方式,使智能Agent具有动态环境的在线学习能力,有效期能够有效地满足Agent各种心智要求。     

基于中介Agent的强化学习优化协商模型

提出了一种基于强化学习的双边优化协商模型。引入了一个中介Agent。在强化学习策略中使用不同的参数产生提议,进而选出最好的参数进行协商。为了进一步提高协商的性能,还提出了基于中介Agent自适应的学习能力。仿真实验结果证明了所提协商方法的有效性,且该方法提高了协商的性能。     

网上自主学习的探索和实践

简要分析了当前学生借助计算机、网络来自主学习面临的问题,推出一个以知识点贯穿始终的自主学习导航系统,研究知识点结构,利用AOE-网和学习资源来解决自主学习中的"迷路"和"无助"问题,并对该系统进行了分析和功能划分。实践证明该系统能有效地解决上述问题。     

A reinforcement learning optimized negotiation method based on mediator agent

This paper firstly proposes a bilateral optimized negotiation model based on reinforcement learning. This model negotiates on the issue price and the quantity, introducing a mediator agent as the mediation mechanism, and uses the improved reinforcement learning negotiation strategy to produce the optimal proposal. In order to further improve the performance of negotiation, this paper then proposes a negotiation method based on the adaptive learning of mediator agent. The simulation results show that the proposed negotiation methods make the efficiency and the performance of the negotiation get improved.     

The effects of organizational learning environment factors on e-learning acceptance

Workplace learning is an important means of employees’ continuous learning and professional development. E-learning is being recognized as an important supportive practice for learning at work. Current research on the success factors of e-learning in the workplace has emphasized on employees’ characteristics, technological attributes, and training design elements, with little attention to workplace contextual effects. The study aims to investigate the impacts of organizational learning environment factors, including managerial support, job support, and organizational support, on employees’ motivation to use a workplace e-learning system. A model was proposed based on the expectancy theory of training motivation and the social influences and facilitating conditions in technology acceptance models. The model was tested on sample data collected from mainland China using Structural Equation Modeling and Moderated Structural Equation Modeling. The results suggested that employees’ perceived managerial support and job support had a significant impact on their perceived usefulness of the e-learning system for individual learning, and that perceived organizational support had a significant influence on the perceived usefulness of the e-learning system for social learning. Perceived usefulness for individual learning was found to completely mediate the environmental influences on individuals’ motivation to use the system, while perceived usefulness for social learning made partial mediation in the effects of the environmental factors on intention to use. In addition, perceived job support was found to have moderating effects on the relationship between employees’ perceived usefulness of the e-learning system and their intention to use the system. Consistent with previous findings, employees’ perceptions about the usefulness of the e-learning system have significant effects on their intention to use the system in the work setting.     

以学习理论探讨基于全球标准数字学习与测评的系统架构及有效学习模式的实证分析

本文通过研究学习理论探讨了ICT信息与网络通讯核心能力常用应用软件适性学习系统的架构。首先就IC3学习系统与精熟学习理论、适性学习理论、鹰架学习理论、示例学习理论及双代码学习理论基础进行了说明,其次利用学生学习数据进行IC3 M-B(Mentor-Benchmark)学习模式的实证性分析,最后就IC3常用应用软件适性学习系统对目前ICT信息与网络通讯技术能力的教学模式、策略以及未来的努力方向提出建议。     

Learning model for adaptive behaviors as an organized group of swarm robots

This paper describes a novel organizational learning model for multiple adaptive robots. In this model, robots acquire their own appropriate functions through local interactions among their neighbors, and get out of deadlock situations without explicit control mechanisms or communication methods. Robots also complete given tasks by forming an organizational structure, and improve their organizational performance. We focus on the emergent processes of collective behaviors in multiple robots, and discuss how to control these behaviors with only local evaluation functions, rather than with a centralized control system. Intensive simulations of truss construction by multiple robots gave the following experimental results: (1) robots in our model acquire their own appropriate functions and get out of deadlock situations without explicit control mechanisms or communication methods; (2) robots form an organizational structure which completes given tasks in fewer steps than are needed with a centralized control mechanism. This work was presented, in part, at the Second International Symposium on Artificial Life and Robotics, Oita, Japan, February 18–20, 1997     

Development of an adaptive learning system with two sources of personalization information

Previous research of adaptive learning mainly focused on improving student learning achievements based only on single-source of personalization information, such as learning style, cognitive style or learning achievement. In this paper, an innovative adaptive learning approach is proposed by basing upon two main sources of personalization information, that is, learning behavior and personal learning style. To determine the initial learning styles of the students, the [Keefe, J. W. (1987). Learning Styles: Theory and Practice. Reston, VA: National Association of Secondary School Principals.] questionnaire is employed in our approach. To more precisely reflect the learning behaviors of each student, the interactions and learning results of each student are analyzed when adjusting the subject materials. Based on the innovative approach, an adaptive learning system has been developed; moreover, an experiment was conducted to evaluate the performance of our approach. By analyzing the results from three groups of students using different adaptive learning approaches, it can be found that the innovative approach is helpful in improving both the learning achievement and learning efficiency of individual students.