Toward Self‐Motivated,Cognitive, Continually Planning Agents

We present a flexible initial framework for defining self‐motivated, self‐aware agents in simulated worlds, planning continuously so as to maximize long‐term rewards. While such agents employ reasoned exploration of feasible sequences of actions and corresponding states, they also behave opportunistically and recover from failure, thanks to their continual plan updates and quest for rewards. Our framework allows for both specific and general (quantified) knowledge and for epistemic predicates such as knowing‐that and knowing‐whether. Because realistic agents have only partial knowledge of their world, the reasoning of the proposed agents uses a weakened closed‐world assumption; this has consequences for epistemic reasoning, in particular introspection. The planning operators allow for quantitative, gradual change and side effects such as the passage of time, changes in distances and rewards, and language production, using a uniform procedural attachment method. Question answering (involving introspection) and experimental runs are shown for our particular agent ME in a simple world, demonstrating the value of continual deliberate, reward‐driven planning. Though the primary merit of agents definable in our framework is that they combine all of the aforementioned features, they can also be configured as single or multiple goal‐seeking agents and as such perform comparably with some recent experimental agents.     

基于VCG机制的动态频谱分配算法

针对在Underlay频谱共享方式下的认知无线网络动态频谱分配问题,在满足主用户服务质量（QoS）的前提下,建立一种非合作博弈模型,并设计其效用函数。在借鉴VCG机制的基础上,设计相应的收益函数,提出一种可以最大化认知无线网络系统吞吐量且保证公平性的分布式动态频谱分配算法。仿真结果表明,该算法收敛速度快、公平性强。     

基于PCA与主动学习AdaBoost的频谱感知算法

针对认知网络中各低信噪比环境下主用户信号检测率偏低的问题,提出一种基于主成分分析和主动学习AdaBoost的主用户信号频谱感知算法.该算法首先采用主成分分析算法对信号特征参数进行提取,获得信号的主成分,之后利用主动学习算法通过多次迭代抽样,获取有利于提高分类性能的样本,并对AdaBoost分类器进行训练,最后利用训练完成的AdaBoost分类器对待测信号进行分类检测.仿真实验表明,在各低信噪比情况下与ANN和MME算法相比较,所提算法具有较高的分类感知性能,有效地实现了对主用户信号的频谱感知.     

认知无线电网络中基于排队论的集中式频谱分配策略

传统的基于图着色模型和基于博弈论模型的动态频谱分配算法因存在计算复杂度高、收敛速度慢等缺陷,在实际网络环境中会造成很大的时延和能耗开销。针对主次用户共存,主用户交替转移忙闲状态的网络环境下,基于排队论模型提出了一种高效、低能耗的集中式频谱分配方案,并给出了该方案下次要用户的平均阻塞率和强制中断率的解析表达式。理论分析和仿真结果表明,所提的方案能够大幅度降低节点能耗。     

基于多角度多层次的认知无线电网络安全研究

认知无线电(Cognitive Radio)技术是为了解决无线网络中频谱资源短缺问题而提出来的新兴技术,它的提出有效的缓解了频谱资源短缺问题,但同时也引入了特有的安全威胁,针对认知无线的特点,从整体架构、协议栈和认知行为的多个角度和层次,研究其在无线网络中引入的安全隐患和已有的解决方案,并对认知无线电安全问题做进一步的展望.     

动态阈值的双门限协作感知方法

随着通信技术的提高和通信应用的增多,无线频谱资源越来越匮乏.许多分配到资源的主用户利用率很低,认知无线电技术希望没有分配到资源的次用户合理使用主用户频谱来提高频谱的利用率.频谱感知技术关系到认知无线电中次用户对空闲频谱的使用机会,是认知无线电的关键技术之一.就是在已有的感知技术的基础上,提出了新的感知手段.在认知无线电网络中,不同的次用户由于与主用户距离以及自身所处环境的噪声影响不同,它们的信噪比一般是不一样的.这里采用的动态阈值的双门限协作感知方法,是对传统双门限能量感知方法的改进,通过充分考虑次用户之间的差异性来提高感知的性能.首先,根据对检测和虚警概率的要求,过滤掉一部分检测能力不满足条件的次用户.同时,每个次用户的用于能量感知的双门限会根据它们各自信噪比的不同而动态变化.通过与单门限能量感知以及传统双门限能量感知方法进行比较,可以看出本文提出的感知方法一定程度上提高了系统整体感知的性能.     

认知无线电网络中安全的协作频谱检测算法

在认知无线电网络中,当认知用户存在虚假感知信息SSDF时,协作频谱感知的性能会受到巨大影响。为了确保频谱感知的鲁棒性,提出了一种基于信誉度加权序贯频谱检测算法来识别恶意用户并减轻他们造成的影响。该算法通过使用认知用户的近期感知信息计算本地信誉度函数,再综合考虑其信誉值与感知过程中表现的稳定程度以消除恶意用户对主用户的传输效率带来的影响。仿真结果表明,在恶意攻击环境下,新算法优于现有典型协作频谱感知算法。     

认知无线网络中基于信誉度管理的动态频谱接入研究

随着无线服务和相关设备的飞速发展,认知无线网络中特有频谱稀缺问题越来越引起研究者的重视。在集中式认知无线网络中,次级用户基站SUBS作为融合中心,通过收到周围的次级用户的感知信息来分配频谱资源。然而,环境的易变性使次级用户容易受到攻击从而影响次级用户感知信息,导致网络频谱资源分配错误。引入信誉度模型来表现次级用户在认知循环中的行为规范,在分配频谱阶段将信誉度作为评定标准,鼓励次级用户积极感知及规范运行。在感知阶段,次级用户感知信道数越多,感知信息越正确,其信誉度越高。在运行阶段,次级用户行为越符合网络规范,则信誉度越高。仿真结果表明,论文模型可以很好地减少次级用户基站的错误决策次数,提高其抗攻击性,同时使得网络在很好地分配资源的同时鼓励整个网络行为积极化。     

Applying Learning Style Theory to Web Page Design

ABSTRACT

Library Web sites can be instructional tools, especially for those patrons who utilize library resources from their homes. Many libraries are developing online tutorials, but there is an opportunity for Web instruction on another level. The organization and design of a Web site can act as an instructional tool in itself. This paper is a call to library Web designers to assess their work in terms of learning style preferences. Learning style theory is based on how people process information and learn new material. Applying these ideas to Web page design can make library resources more accessible and improve the patron's comprehension of how the library works.     

Cognitive evaluation for conceptual design: cognitive role of a 3D sculpture tool in the design thinking process

ABSTRACT

This study focuses on the decisive role played by the digital design environment in the cognitive design process and design thinking. To analyse the cognitive role of digital design tools, we carried out a protocol analysis of conventional design sketching and a 3D sculpture tool. Cognitive evaluation was a differentiating factor when considering the contextual role of the 3D sculpture tool in subsequent evaluations, non-sequential evaluations for conversion, and passive approaches within the design process. Cognitive evaluation played the following roles: validation, extension, navigation, exploration, and confirmation. The navigation, exploration, and extension roles played by non-sequential evaluation were mainly related to inductive design thinking. Finally, the types of cognitive evaluation and their roles when using the 3D sculpture tool were different, according to the design thinking type. This study explored the multidimensional roles of cognitive evaluation using a 3D sculpture tool and its relationship with design thinking types.