Toward a programming theory for rational agents

An important problem in agent verification is a lack of proper understanding of the relation between agent programs on the one hand and agent logics on the other. Understanding this relation would help to establish that an agent programming language is both conceptually well-founded and well-behaved, as well as yield a way to reason about agent programs by means of agent logics. As a step toward bridging this gap, we study several issues that need to be resolved in order to establish a precise mathematical relation between a modal agent logic and an agent programming language specified by means of an operational semantics. In this paper, we present an agent programming theory that provides both an agent programming language as well as a corresponding agent verification logic to verify agent programs. The theory is developed in stages to show, first, how a modal semantics can be grounded in a state-based semantics, and, second, how denotational semantics can be used to define the mathematical relation connecting the logic and agent programming language. Additionally, it is shown how to integrate declarative goals and add precompiled plans to the programming theory. In particular, we discuss the use of the concept of higher-order goals in our theory. Other issues such as a complete axiomatization and the complexity of decision procedures for the verification logic are not the focus of this paper and remain for future investigation. Part of this research was carried out while the first author was affiliated with the Nijmegen Institute for Cognition and Information, Radboud University Nijmegen.     

A comprehensive decision making structure for partitioning of make-to-order, make-to-stock and hybrid products

Manufacturing systems produce their products by making use of three main strategies: make-to-order, make-to-stock and hybrid (combination of MTO and MTS strategies) systems. Hence, several products must be considered and partitioned in terms of many different conflicting criteria, leading to a large set of subjective or ambiguous data. Thus, an effective evaluation approach is essential to improve decision quality. In this paper a comprehensive decision, making structure is proposed to choose the proper strategy for producing the products. It consists of a novel hybrid methodology, which combines analytical hierarchy process (AHP) and technique for order performance by similarity to ideal solution (TOPSIS) for partitioning of products. In this study, the rating of each alternative regarding different criteria (throughout the TOPSIS technique) is described by means of linguistic variables. Furthermore, fuzzy AHP methodology is applied to determine the weights of evaluation criteria. At the end, the effectiveness of the proposed model is demonstrated through a case study.     

The pedagogical challenges to collaborative technologies

Collaborative technologies offer a range of new ways of supporting learning by enabling learners to share and exchange both ideas and their own digital products. This paper considers how best to exploit these opportunities from the perspective of learners’ needs. New technologies invariably excite a creative explosion of new ideas for ways of doing teaching and learning, although the technologies themselves are rarely designed with teaching and learning in mind. To get the best from them for education we need to start with the requirements of education, in terms of both learners’ and teachers’ needs. The argument put forward in this paper is to use what we know about what it takes to learn, and build this into a pedagogical framework with which to challenge digital technologies to deliver a genuinely enhanced learning experience.     

Denial of service attacks and defenses in decentralized trust management

Trust management is an approach to scalable and flexible access control in decentralized systems. In trust management, a server often needs to evaluate a chain of credentials submitted by a client; this requires the server to perform multiple expensive digital signature verifications. In this paper, we study low-bandwidth Denial-of-Service (DoS) attacks that exploit the existence of trust management systems to deplete server resources. Although the threat of DoS attacks has been studied for some application-level protocols such as authentication protocols, we show that it is especially destructive for trust management systems. Exploiting the delegation feature in trust management languages, an attacker can forge a long credential chain to force a server to consume a large amount of computing resource. Using game theory as an analytic tool, we demonstrate that unprotected trust management servers will easily fall prey to a witty attacker who moves smartly. We report our empirical study of existing trust management systems, which manifests the gravity of this threat. We also propose a defense technique using credential caching, and show that it is effective in the presence of intelligent attackers. A preliminary version of this paper was presented at the Second IEEE International Conference on Security and Privacy in Communication Networks, Baltimore, MD, USA, August 2006.     

D-S证据理论在移动机器人信息融合中的应用

移动机器人的自动能力中实时避障和导航是一个很关键的技术,研究中主要的问题是：机器人在运动时需要充分的环境信息,而且处理这些信息的速度要快,同时也要满足实时性的要求。详细介绍了将D-S证据理论应用于移动机器人对未知环境的探索、感知过程,并通过仿真结果对D-S证据融合方法的性能进行研究与改进,确定了D-S证据融合方案的具体实现步骤,并完成了一个简化的仿真算例,得出了相关结论。     

Controller synthesis with guaranteed closed-loop phase constraints

In this paper, we present an analysis and synthesis approach for guaranteeing that the phase of a single-input, single-output closed-loop transfer function is contained in the interval [−α,α] for a given α>0 at all frequencies. Specifically, we first derive a sufficient condition involving a frequency domain inequality for guaranteeing a given phase constraint. Next, we use the Kalman–Yakubovich–Popov theorem to derive an equivalent time domain condition. In the case where , we show that frequency and time domain sufficient conditions specialize to the positivity theorem. Furthermore, using linear matrix inequalities, we develop a controller synthesis approach for guaranteeing a phase constraint on the closed-loop transfer function. Finally, we extend this synthesis approach to address mixed gain and phase constraints on the closed-loop transfer function.     

一种基于充要强度的优化规则发现方法

提出了一种基于信息系统的优化规则的提取方法,主要目的是提取信息系统中具有一定充要性的优化规则。首先,提出了充要强度并讨论了它的性质。其次,由于搜索空间的巨大和遗传算法的全局优化的特性,设计了使用遗传算法进行优化规则搜索的方法。最后,通过实验说明方法的有效性。     

粗糙集理论的双重学习方法研究

提出了一种新的粗糙集双重学习方法,该方法能用遗传算法实现外层学习,用规则提取方法进行内层学习．其基本思想是：首先引入遗传算法,将属性编码,并针对不同的属性组合进行规则提取;然后用测试样本对规则集进行检验,并基于所得到的识别率建立适应度函数;最后在合适的遗传算子下获取最佳的属性组合及相应的知识规则．与其他方法相比,本文所提粗糙集双重学习方法集属性约简和规则提取于一体,整个过程具有很强的自适应能力．最后,用算例对本文方法进行了验证．     

基于贝叶斯理论的图像标注和检索

图像自动语义标注是基于内容图像检索中很重要且很有挑战性的工作.提出用语义约束的聚类方法对分割后的图像区域进行聚类,在图像标注阶段,使用贪心选择连接(GSJ)算法找出聚类区域的独立子集,然后使用贝叶斯理论进行语义标注.对图像进行标注以后,使用标注的关键字进行检索.在一个包含500幅图像的图像库进行实验,结果表明,提出的方法具有较好的检索性能.     

3-gated：WLAN中基于负载自适应的动态调度机制

本文针对实时业务在网络负载增加情况下的特点,改进了文[3]的结果,提出了一种新的无线网络MAC层动态调度机制:3-gated调度算法.该机制实现简单,并且可以在不改变现有协议构架甚至不增加开销的基础上较好解决实时业务在网络负载加大环境下用户时延QoS不能得到满足的问题.运用嵌入式马尔可夫链理论和多维概率母函数的方法对该算法进行建模,得到了改进后网络队列缓存的平均排队队长和信息分组平均时延理论解析式.通过仿真验证了理论分析的有效性,表明3-gated算法性能十分接近对称业务最优算法--完全服务调度算法,并避免了后者公平性差的弊端.