软件构架动态行为建模与检测

针对软件构架描述语言在分析、验证软件构架动态行为中的不足,用抽象代数对构件、连接器和体系结构配置进行抽象,提出了软件构架层次模型,并采用Pr／T网对软件构架动态行为建模．提出基于线性时序逻辑的软件构架动态行为模型检测方法,给出了该方法的算法描述．最后,详细描述了电子商务系统中并发控制机制的建模过程和检测结果．提出的软件构架动态行为建模与检测方法结合了Pr／T网和线性时序逻辑的优点,为开展软件构架动态行为的分析、验证提供了理论基础．     

Model checking rational agents

Agent-oriented programming techniques seem appropriate for developing systems that operate in complex, dynamic, and unpredictable environments. We aim to address this requirement by developing model-checking techniques for the (automatic or semiautomatic) verification of rational-agent systems written in a logic-based agent-oriented programming language. Typically, developers apply model-checking techniques to abstract models of a system rather than the system implementation. Although this is important for detecting design errors at an early stage, developers might still introduce errors during coding. In contrast, developers can directly apply our model-checking techniques to systems implemented in an agent-oriented programming language, automatically verifying agent systems without the usual gap between design and implementation. We developed our techniques for AgentSpeak, a rational-agent programming language based on the AgentSpeak (L) abstract agent-oriented programming language. AgentSpeak shares many features of the agent-oriented programming paradigm. Similarly, we've developed techniques for automatically translating AgentSpeak programs into the model specification language of existing model-checking systems. In this way, we reduce the problem of verifying that an AgentSpeak system has certain BDI logic properties to a conventional LTL model-checking problem.     

Applying Propositional Logic to Workflow Verification

The increasing complexity of business processes in the era of e-business has heightened the need for workflow verification tools. However, workflow verification remains an open and challenging research area. As an indication, most of commercial workflow management systems do not yet provide workflow designers with formal workflow verification tools. We propose a logic-based verification method that is based on a well-known formalism, i.e., propositional logic. Our logic-based workflow verification approach has distinct advantages such as its rigorous yet simplistic logical formalism and its ability to handle generic activity-based process models. In this paper, we present the theoretical framework for applying propositional logic to workflow verification and demonstrate that logic-based workflow verification is capable of detecting process anomalies in workflow models.     

A logical approach to knowledge based control

Future increase in industrial productivity will stem, in large measure, from the effective utilization of automation technologies in the manufacturing environment. Although many tools exist for process automation in both hardware capabilities and software techniques, they have been applied to date only in restricted environments and for limited applications. To fully reap the benefits of the technological state of the art, isolated capabilities must be integrated into a synergistic whole.This paper demonstrates how a logic-based approach can provide both a practical and a theoretical foundation for such integration. From a theoretical standpoint, a coherent framework build on logic-based techniques is indicated. A promising structure within this arena is modal logic, which serves to integrate other methodologies such as temporal logic. Further, the power of this approach as a formalizing tool is shown. In particular, the formalization can provide a rigorous structure for investigating the theoretical limits as well as efficiency issues.From a practical standpoint, the methods of logic can serve as a substrate for integrating diverse representation techniques. More specifically, the integration of qualitative and quantitative knowledge is studied. Previous work in qualitative physics as well as concepts such as the superinterval, which effectively combines point-based and interval-based temporal reasoning techniques, can be utilized. The major advantage of an integrated approach is the feasibility of developing model-based control systems. As a result, various activities such as process planning, error diagnosis, and fault management can proceed through a chain of causal inferences rather than merely stand as a superficial set of decision rules. In this way, the control system can check for internal consistency and even reason about some eventualities which were not necessarily envisioned by the original developers. The utility of this integrated, model-based approach is investigated using case studies.     

A survey of recent advances in fuzzy logic in telecommunicationsnetworks and new challenges

The use of fuzzy logic in telecommunication systems and networks is recent and limited. Fundamentally, Zadeh's fuzzy set theory provides a robust mathematical framework for dealing with “real-world” imprecision and nonstatistical uncertainty. Given that the present day complex networks are dynamic, that there is great uncertainty associated with the input traffic and other environmental parameters, that they are subject to unexpected overloads, failures and perturbations, and that they defy accurate analytical modeling, fuzzy logic appears to be a promising approach to address many important aspects of networks. This paper reviews the current research efforts in fuzzy logic-based approaches to queuing, buffer management, distributed access control, load management, routing, call acceptance, policing, congestion mitigation, bandwidth allocation, channel assignment, network management, and quantitative performance evaluation in networks. The review underscores the future potential and promise of fuzzy logic in networks. The paper then presents a list of key research efforts in the areas of fuzzy logic-based algorithms and new hardware and software architectures that are necessary both to address new challenges in networking and to help realize the full potential of fuzzy logic in networks     

From linear temporal logic and limit-deterministic Büchi automata to deterministic parity automata

Controller synthesis for general linear temporal logic (LTL) objectives is a challenging task. The standard approach involves translating the LTL objective into a deterministic parity automaton (DPA) by means of the Safra-Piterman construction. One of the challenges is the size of the DPA, which often grows very fast in practice, and can reach double exponential size in the length of the LTL formula. In this paper, we describe a single exponential translation from limit-deterministic Büchi automata (LDBA) to DPA and show that it can be concatenated with a recent efficient translations from LTL to LDBA to yield a double exponential, ‘Safraless’ LTL-to-DPA construction. We also report on an implementation and a comparison with other LTL-to-DPA translations on several sets of formulas from the literature.

     

Probabilistic modelling, inference and learning using logical theories

This paper provides a study of probabilistic modelling, inference and learning in a logic-based setting. We show how probability densities, being functions, can be represented and reasoned with naturally and directly in higher-order logic, an expressive formalism not unlike the (informal) everyday language of mathematics. We give efficient inference algorithms and illustrate the general approach with a diverse collection of applications. Some learning issues are also considered.     

Probabilistic rule-based argumentation for norm-governed learning agents

This paper proposes an approach to investigate norm-governed learning agents which combines a logic-based formalism with an equation-based counterpart. This dual formalism enables us to describe the reasoning of such agents and their interactions using argumentation, and, at the same time, to capture systemic features using equations. The approach is applied to norm emergence and internalisation in systems of learning agents. The logical formalism is rooted into a probabilistic defeasible logic instantiating Dung??s argumentation framework. Rules of this logic are attached with probabilities to describe the agents?? minds and behaviours as well as uncertain environments. Then, the equation-based model for reinforcement learning, defined over this probability distribution, allows agents to adapt to their environment and self-organise.     

时态描述逻辑ALC-LTL的Tableau判定算法

时态描述逻辑ALC-LTL将描述逻辑ALC的描述能力与线性时态逻辑LTL的刻画能力结合起来,在具有较强描述能力的同时还使得可满足性问题保持在EXPTIME-完全这个级别。针对ALC-LTL缺少有效的判定算法的现状,将LTL的Tableau判定算法与描述逻辑ALC的推理机制有机地结合起来,给出了ALC-LTL的Tableau判定算法并证明了算法的可终止性、可靠性和完备性。该算法具有很好的可扩展性。当ALC-工`I'I、中的描述逻辑从ALC改变为任何一个具有可判定性特征的描述逻辑X时,只需要对算法进行简单修改,就可以得到相应的时态描述逻辑X-LTL的Tableau判定算法。     

一种新的安全协议形式化分析方法——证据逻辑

形式化分析技术对于安全协议的正确设计至关重要,考虑到现有信仰逻辑分析方法的不足,该文提出一种新的安全协议形式化分析方法——证据逻辑,即通过对协议主体证据的推理来实现安全协议的形式化分析。与现有的方法相比,该方法不仅能够用于认证协议、密钥协商(交换)协议的分析,也能用于电子商务协议的不可否认性和公平性的分析,因此具有更好的通用性和更强的协议分析能力。     

SEQUENCE-INDEXED LINEAR-TIME TEMPORAL LOGIC: PROOF SYSTEM AND APPLICATION

We propose a proof system for reasoning on certain specifications of secure authentication systems. For this purpose, a new logic, sequence-indexed linear-time temporal logic (SLTL), is obtained semantically from standard linear-time temporal logic (LTL) by adding a sequence modal operator that represents a sequence of symbols. By this sequence modal operator, we can appropriately express message flows between clients and servers and states of servers in temporal reasoning. A Gentzen-type sequent calculus for SLTL is introduced, and the completeness and cut-elimination theorems for it are proved. SLTL is also shown to be PSPACE-complete and embeddable into LTL.     

Foundations for using linear temporal logic in Event-B refinement

In this paper we present a new way of reconciling Event-B refinement with linear temporal logic (LTL) properties. In particular, the results presented in this paper allow properties to be established for abstract system models, and identify conditions to ensure that the properties (suitably translated) continue to hold as those models are developed through refinement. There are several novel elements to this achievement: (1) we identify conditions that allow LTL properties to be mapped across refinement chains; (2) we provide translations of LTL predicates to reflect the introduction through refinement of new events and the renaming and splitting of existing events; (3) we do this for an extended version of LTL particularly suited to Event-B, including state predicates and enabledness of events, which can be model-checked at the abstract level. Our results are more general than any previous work in this area, covering liveness in the context of anticipated events, and relaxing constraints between adjacent refinement levels. The approach is illustrated with a case study. This enables designers to develop event based models and to consider their execution patterns so that liveness and fairness properties can be verified for Event-B systems.     

A linear translation from CTL* to the first-order modal μ -calculus

The modal μ-calculus is a very expressive temporal logic. In particular, logics such as LTL, CTL and CTL* can be translated into the modal μ-calculus, although existing translations of LTL and CTL* are at least exponential in size. We show that an existing simple first-order extension of the modal μ-calculus allows for a linear translation from LTL. Furthermore, we show that solving the translated formulae is as efficient as the best known methods to solve LTL formulae directly.     

协同业务过程与需求的建模及一致性验证

自底向上建模方法中的业务过程由不同组织开发,无法在设计阶段就预见其潜在的所有交互可能.因此,在实际协作中,建立协同业务过程可能与参与组织期望的系统功能和特性不一致.为此,提出一种协同业务过程与需求的建模及一致性验证方法.首先,引入并发操作符,提供一种通过组合参与组织的业务过程构建协同业务过程方法;然后,扩展目标模型,提出需求依赖图来建模参与组织的需求;最后,基于模型检测技术提出协同业务过程与需求一致性检测方法.重点解决了将协同业务过程转换为表达能力相同FSP进程规约和参与组织需求转换为LTL公式这两个问题.通过对典型的协同业务过程集阐述提出方法的有效性,并对方法分析效率进行评价,结果表明：相对已有工作,提出方法能够更加有效地用于协同业务过程与需求的一致性分析.     

线性时序逻辑引导的安全强化学习

针对动态不确定环境下机器人执行复杂任务的需求,提出一种线性时序逻辑(linear temporal logic, LTL)引导的无模型安全强化学习算法,能在最大化任务完成概率的同时保证学习过程的安全性.首先,综合考虑环境中的不确定因素,构建马尔可夫决策过程(Markov decision process, MDP),再用LTL刻画智能体的复杂任务,将其转化为有多接受集的基于转移的有限确定性广义布奇自动机(transition-based limit deterministic generalized Büchi automaton, t LDGBA),并通过接受边界函数构建可记录当前待访问接受集的约束型tLDGBA (constrained tLDGBA,ctLDGBA);其次,构建乘积MDP用于强化学习搜索最优策略;最后,基于LTL对安全性的描述和MDP的观测函数构建安全博弈,并根据安全博弈设计安全盾机制保证系统在学习过程中的安全性.严格的分析证明了所提出的算法能获得最大化LTL任务完成概率的最优策略.仿真结果验证了LTL引导的安全强化学习算法的有效性.     

在NiosⅡ系统设计中SignalTabⅡ的应用

通过对Altera公司的SignalTap Ⅱ基于逻辑分析核的嵌入式逻辑分析仪的特点及使用方法的介绍,并结合实例说明SignalTap Ⅱ为SOPC设计,提供了实时可视性,减少了验证过程的时间,     

进程异常检测中淋巴细胞的逻辑语义模型

论文针时反向选择算法无法有效地捕捉某些复杂问题空间的语义信息的缺点,以逻辑程序设计领域中的稳定模型为理论基础,提出一个淋巴细胞的逻辑语义模型。该模型采用逻辑程序表示淋巴细胞和抗原,通过计算它们的稳定模型来进行异常检测。最后,以进程异常检测为背景,设计了一个系统框架。该框架充分考虑了进程系统调用短序列的语义信息。能有效地提高异常检测的准确率。     

面向参数化LTL的预测监控器构造技术

介绍了一种基于自动机理论的参数化LTL(parameterized LTL(linear temporal logic),简称P_ALTL)公式运行时预测监控器构造方法.一方面研究P_ALTL公式的语法、预测语义、赋值提取以及赋值绑定等重要概念,从语法层面保证公式中参数化变量的正确绑定(binding)和使用(using);另一方面给出参数化预测监控器的概念.它由静态和动态两部分组成,静态部分由参数化Büchi自动机表示,动态部分为当前状态处的变量赋值.在系统运行过程中,预测监控器基于静态部分的参数化Büchi自动机,以on-the-fly的方式在当前状态处动态地提取和绑定变量赋值,递进地验证当前程序运行是否满足指定的参数化性质规约.在该过程中,参数化监控器能够精确地识别被验证性质的最小好/坏前缀.