一种求解最小权值强规划的方法

以规划领域中的不确定状态转移系统作为研究对象,给出最小权值强规划解的概念,提出一种求最小权值强规划解的方法.该方法可以求解与动作代价相关的数值规划问题,在不确定状态转移系统的执行动作上增加权值来表示动作的代价,在此基础上设计求解最小权值强规划解的算法.实验结果表明,该算法能有效求解最小权值强规划解,且比用反向搜索方法求...     

一种快速求强规划解的算法

为提高求解效率,设计一种求强规划解的简化分层算法。以传统分层算法为基础,引入贪心选择策略,对每个非目标状态的动作进行筛选,去除对求解强规划解无益的动作,加快状态向下搜索的速度,并在改进分层的基础上,优化求强规划解策略,由于在求解过程中会存在大量重复搜索,因此建立一个集合保存已访问状态的信息,避免对状态的重复搜索。分析结果表明,在初始状态到达目标状态路径都不重合的情况下,改进算法的时间复杂度为O( nm)( n为初始状态个数,m为层数),在都重合情况下为O( m),优于普通正向搜索算法与反向搜索算法。     

JLU-RLAO和JLU-QLAO:两个不确定智能规划求解系统

不确定环境下的智能规划问题往往假设世界状态的转移概率是确切可知的,然而规划建模专家有时只能在信息不完备的条件下进行建模.从而只能通过猜测或者不完全统计的方法来获取不完备的有关状态转移不确定性的定量信息,有时甚至只能荻取相关的定性信息.在2004年概率规划比赛冠军LAO系统的基础上设计了JLU-RLAO系统和JLU-QLAO系统.它们可以在无法获得精确的状态转移概率条件下,依然保证规划求解的健壮性.实验结果表明,JLU-RLAO系统和JLU-QLA0系统可以快速高效地解决上述不确定智能规划问题.     

两层多目标规划的罚函数法

研究了一类非线性两层多目标规划问题.在下层多目标规划问题的目标函数是严格凸函数、决策变量约束集是凸集的假设下,通过将两层多目标规划问题转化成一系列单层多目标规划问题,建立了两层多目标规划的罚函数理论,并进行了收敛性分析.从而丰富了两层多目标规划的理论,为解决实际中的两层多目标决策问题提供了有力的工具.     

动态不确定环境下多目标路径规划方法

提出一种在动态不确定环境下求解多目标问题时快速调整移动路径的方法.首先提出采用逆向多目标启发式搜索进行全局规划,求解问题的最优路径集合;然后提出动态多目标路径规划方法,先根据当前观测进行全局规划,在移动过程中探测到不一致的环境信息时,通过对先前搜索中部分信息的重用,在全局规划的基础上进行增量重规划,调整当前状态与目标状...     

基于扩展字典稀疏表示分类的遥感目标识别

针对遥感图像视觉对比度差、分辨率低及目标含有不同角度旋转的情况,在稀疏表示分类识别的基础上,提出一种基于扩展字典稀疏表示的遥感目标识别方法。首先将训练样本和待测样本进行二进小波变换增强,提取增强图像的SIFT特征构成特征字典,并将原始的训练字典改为训练-特征扩展字典进行稀疏表示,从而使字典更加具有判别能力,提高识别率。同时,分析了SIFT特征经随机投影后对识别率的影响。实验表明,该方法对遥感图像目标识别具有较好的鲁棒性。     

不确定规划中可达关系的快速求解算法

在不确定规划领域中,通常需要在同一个不确定状态转移系统中解决多个规划问题,如果能得到不确定规划中状态之间的可达关系即可方便求解该规划问题,然而现有矩阵乘法求解可达关系时存在算法复杂度高的问题。为此,设计一种快速求解不确定规划中状态之间可达关系的算法,将确定动作和不确定动作区分处理,先求解所有确定动作的可达关系,再采用链表和队列求解不确定动作的可达关系。实验结果表明,与矩阵乘法相比,该算法能得到更全面的可达关系,且求解效率更高。     

基于扩展目标规划图的网络攻击规划识别算法

在人工智能领域经典规划识别方法的基础上，针对网络攻防领域攻击规划识别问题的特性，对目标规划图进行进一步扩充，引入观察节点以区分规划者动作以及识别者对动作的观察，将动作节点分化为由具体动作层和抽象动作层组成的层次结构，并根据抽象攻击模式在抽象攻击层面上维护与安全状态节点的前提和后果条件，形成扩展目标规划图（Extended Goal Graph，EGG）模型；并进一步提出基于扩展目标规划图的攻击规划识别算法，该算法能够有效地从大量底层入侵报警信息中正确识别背后蕴藏的攻击者意图及规划．通过DARPA2000入侵场景关联评测数据集和在蜜网环境中捕获的实际僵尸网络攻击场景数据的实验测试以及与TIAA入侵报警关联分析系统的实验结果对比，验证了该文提出算法的完备性与有效性．     

以目标为导向的时序图规划算法的研究

本文提出了一种从目标集扩张时序规划图的新算法。此算法与现有算法不同。采用逆向扩张、正向搜索的策略：由于扩张保留了关于目标的信息。实现了动作方案的完全量化。在搜索阶段。只搜索相关可用动作的交叉点,减少了搜索代价,极大地提高了搜索效率。     

Markov决策过程的蚁群规划算法

在智能规划问题上,寻找规划解都是NP甚至NP完全问题,如果动作的执行效果带有不确定性,如在Markov决策过程的规划问题中,规划的求解将会更加困难,现有的Markov决策过程的规划算法往往用一个整体状态节点来描述某个动作的实际执行效果,试图回避状态内部的复杂性,而现实中的大量动作往往都会产生多个命题效果,对应多个命题节点。为了能够处理和解决这个问题,提出了映像动作,映像路节和映像规划图等概念,并在其基础上提出了Markov决策过程的蚁群规划算法,从而解决了这一问题。并且证明了算法得到的解,即使在不确定的执行环境下,也具有不低于一定概率的可靠性。     

Bi-inductive Structural Semantics: (Extended Abstract)

We propose a simple order-theoretic generalization of set-theoretic inductive definitions. This generalization covers inductive, co-inductive and bi-inductive definitions and is preserved by abstraction. This allows the structural operational semantics to describe simultaneously the finite/terminating and infinite/diverging behaviors of programs. This is illustrated on the structural bifinitary small/big-step trace/relational/operational semantics of the call-by-value λ-calculus.     

A Rewriting Logic Approach to Operational Semantics (Extended Abstract)

This paper shows how rewriting logic semantics (RLS) can be used as a computational logic framework for operational semantic definitions of programming languages. Several operational semantics styles are addressed: big-step and small-step structural operational semantics (SOS), modular SOS, reduction semantics with evaluation contexts, and continuation-based semantics. Each of these language definitional styles can be faithfully captured as an RLS theory, in the sense that there is a one-to-one correspondence between computational steps in the original language definition and computational steps in the corresponding RLS theory. A major goal of this paper is to show that RLS does not force or pre-impose any given language definitional style, and that its flexibility and ease of use makes RLS an appealing framework for exploring new definitional styles.     

基于ICU的复杂文本布局引擎设计与跨平台应用研究

ICU复杂文本布局引擎与其他应用较为广泛的复杂文本布局引擎相比的一大长处是它的开放源代码.通过分析ICU源码,并以此为基础设计新的复杂文本的布局引擎.首先简要介绍了复杂文本布局引擎的一般原理,然后以复杂文字语言蒙古文为例,详细探讨了基于ICU的复杂文本布局引擎的设计思路和方法,最后对复杂文本布局引擎的跨平台应用进行了深入研究.     

Bounded Model Checking of CTL

Bounded Model Checking has been recently introduced as an efficient verification method for reactive systems. This technique reduces model checking of linear temporal logic to propositional satisfiability. In this paper we first present how quantified Boolean decision procedures can replace BDDs. We introduce a bounded model checking procedure for temporal logic CTL＊ which reduces model checking to the satisfiability of quantified Boolean formulas. Our new technique avoids the space blow up of BDDs, and extends the concept of bounded model checking.     

引擎设计与跨平台应用研究*

ICU复杂文本布局引擎与其他应用较为广泛的复杂文本布局引擎相比的一大长处是它的开放源代码。通过分析ICU源码,并以此为基础设计新的复杂文本的布局引擎。首先简要介绍了复杂文本布局引擎的一般原理,然后以复杂文字语言蒙古文为例,详细探讨了基于ICU的复杂文本布局引擎的设计思路和方法,最后对复杂文本布局引擎的跨平台应用进行了深入研究。     

A viral infection model with periodic immune response and nonlinear CTL response

This paper investigates a viral infection model with periodic immune response and nonlinear cytotoxic T lymphocyte (CTL) response. Using the periodic rhythms of human immune system, the model can avoid the unreasonable equilibrium in the basic viral model with nonlinear CTL response introduced by Nowak et al. We obtain the global stability of the infection-free equilibrium and the immune-exhausted equilibrium. Numerical simulations show that the oscillation of immune system can affect the pattern of the viral dynamical behaviors. Period doubling bifurcations of the system are observed via simulations. This can provide a possible interpretation for the viral oscillation behaviors, which were observed in chronic HBV and HCV infection patients.     

Extended Semantics and Optimization Algorithms for CP-Networks

Preference elicitation is a serious bottleneck in many decision support applications and agent specification tasks. Ceteris paribus (CP)-nets were designed to make the process of preference elicitation simpler and more intuitive for lay users by graphically structuring a set of CP preference statements—preference statements that most people find natural and intuitive. Beside their usefulness in the process of preference elicitation, CP-nets support efficient optimization algorithms that are crucial in most applications (e.g., the selection of the best action to execute or the best product configuration). In various contexts, CP-nets with an underlying cyclic structure emerge naturally. Often, they are inconsistent according to the current semantics, and the user is required to revise them. In this paper, we show how optimization queries can be meaningfully answered in many "inconsistent" networks without troubling the user with requests for revisions. In addition, we describe a method for focusing the user's revision process when revisions are truly needed. In the process, we provide a formal semantics that justifies our approach and new techniques for computing optimal outcomes. Some of the methods we use are based on a reduction to the problem of computing stable models for nonmonotonic logic programs, and we explore this relationship closely.     

A Calculus for Reconfiguration: (Extended abstract)

We present a simple calculus, called R-calculus (for “reconfiguration”), intended to provide a kernel model for a computational paradigm in which standard execution (that is, execution of a single computation described by a fragment of code) can be interleaved with operations at the meta-level which can manipulate in various ways the context in which this computation takes place. Formally, this is achieved by introducing as basic terms of the calculus configurations, which are, roughly speaking, pairs consisting of an (open, mutually recursive) collection of named components and a term representing a program running in the context of these components. The R-calculus has been originally developed as a formal model for programming-in-the large, where computations correspond to applications running in some context of software components, and operations at the meta-level correspond to the possibility of dynamically loading, updating or in general manipulat- ing these software components without stopping the application. However, the calculus can also encode programming-in-the-small issues, because configurations combine the features of lambda- abstractions (first-class functions), records, environments with mutually recursive definitions, and modules. We state confluence of the calculus and define a call-by-need strategy which leads to a generalization, including reconfiguration features, of call-by-need lambda-calculi.     

Improving state class constructions for CTL* model checking of time Petri nets

The state space explosion is still one of the most challenging problems in formal verification using enumerative techniques. The challenge is even greater for real time systems whose state spaces are generally infinite due to time density. To use enumerative techniques with these systems, their state spaces need to be contracted into finite structures that preserve properties of interest. We propose in this paper an efficient approach to construct a contraction of the time Petri net model state space, which preserves its CTL* properties.