不完备信息的航空电子装备诊断规则提取方法

针对不完备信息引发的不确定性给航空电子装备的诊断规则提取带来的挑战,分别从广义狭义两个角度对故障诊断决策系统的不完备性进行定义,设计了一致性优先的相似度及属性值期望最大的缺失信息补齐算法,解决间接补齐算法存在不一致性问题;构建征兆属性概念格及诊断决策属性概念格,生成不完备诊断决策信息系统的扩充辨识矩阵,引入征兆属性概念等价关系计算最大一致征兆概念集,求解最大一致征兆概念辨识函数的析取范式获取最优约简属性集,根据约简后的诊断决策信息系统获取诊断规则。以某型航空装备的武器系统发射系统为例对方法验证,诊断结果准确率达到83.3%,高于现有典型方法,该方法在不完备信息处理、精确度及对象描述的直观简洁性方面具有显著优势。     

Incompleteness of conversion in a traveling polymerization wave in the presence of heat loss

The steady-state propagation of a polymerization wave in an infinite bulk is studied. It is assumed that the heat release law is specified by a truncated Arrhenius function. It is shown that in the presence of heat loss, complete conversion of the substance is impossible. __________ Translated from Fizika Goreniya i Vzryva, Vol. 43, No. 6, pp. 75–77, November–December, 2007.     

Extrapolation of fuzzy values from incomplete data bases

This paper presents different approaches which enable a data base management system to obtain a plausible fuzzy estimate for an attribute value of an item for which the information is not explicitly stored in the data base. This can be made either by a kind of analogical reasoning from information about particular items or by means of expert rules which specify the (fuzzy) sets of possible values of the attribute under consideration, for various classes of items. Another kind of expert rules enables the system to compute an estimate from the attribute value of another item provided that, in other respects, this latter item sufficiently resembles the item, the value of which we are interested in; then these expert rules are used either for controlling the analogical reasoning process or for enlarging the scope of application of the first kind of expert rules. The different approaches are discussed in the framework of possibility theory.     

Constructive belief and rational representation

It is commonplace in artificial intelligence to divide an agent's explicit beliefs into two parts: the beliefs explicitly represented or manifest in memory, and the implicitly represented or constructive beliefs that are repeatedly reconstructed when needed rather than memorized. Many theories of knowledge view the relation between manifest and constructive beliefs as a logical relation, with the manifest beliefs representing the constructive beliefs through a logic of belief. This view, however, limits the ability of a theory to treat incomplete or inconsistent sets of beliefs in useful ways. We argue that a more illuminating view is that belief is the result of rational representation. In this theory, the agent obtains its constructive beliefs by using its manifest beliefs and preferences to rationally (in the sense of decision theory) choose the most useful conclusions indicated by the manifest beliefs.     

Incompleteness,Complexity, Randomness and Beyond

Gödel's Incompleteness Theorems have the same scientific status as Einstein's principle of relativity, Heisenberg's uncertainty principle, and Watson and Crick's double helix model of DNA. Our aim is to discuss some new faces of the incompleteness phenomenon unveiled by an information-theoretic approach to randomness and recent developments in quantum computing.     

Computationalism

Computationalism, the notion that cognition is computation, is a working hypothesis of many AI researchers and Cognitive Scientists. Although it has not been proved, neither has it been disproved. In this paper, I give some refutations to some well-known alleged refutations of computationalism. My arguments have two themes: people are more limited than is often recognized in these debates; computer systems are more complicated than is often recognized in these debates. To underline the latter point, I sketch the design and abilities of a possible embodied computer system.     

社会经济系统的灰性及其灰色趋势关联分析

本文深入探讨了社会经济系统的灰性;提出了社会经济系统(SES)的系统云、灰色趋势关联函数、灰色趋势关联度等基本概念;利用因子的特征指数,给出了灰关联空间的一种分解方法;定义了发展子空间、障碍子空间和同步子空间;给出了灰色趋势关联分析的一般步骤,为社会经济系统的灰联联分析提供了新的方法和途径。     

Consistency,Turing Computability and Gödel’s First Incompleteness Theorem

It is well understood and appreciated that Gödel’s Incompleteness Theorems apply to sufficiently strong, formal deductive systems. In particular, the theorems apply to systems which are adequate for conventional number theory. Less well known is that there exist algorithms which can be applied to such a system to generate a gödel-sentence for that system. Although the generation of a sentence is not equivalent to proving its truth, the present paper argues that the existence of these algorithms, when conjoined with Gödel’s results and accepted theorems of recursion theory, does provide the basis for an apparent paradox. The difficulty arises when such an algorithm is embedded within a computer program of sufficient arithmetic power. The required computer program (an AI system) is described herein, and the paradox is derived. A solution to the paradox is proposed, which, it is argued, illuminates the truth status of axioms in formal models of programs and Turing machines.     

Alan Turing and the Mathematical Objection

This paper concerns Alan Turing's ideas about machines, mathematical methods of proof, and intelligence. By the late 1930s, Kurt Gödel and other logicians, including Turing himself, had shown that no finite set of rules could be used to generate all true mathematical statements. Yet according to Turing, there was no upper bound to the number of mathematical truths provable by intelligent human beings, for they could invent new rules and methods of proof. So, the output of a human mathematician, for Turing, was not a computable sequence (i.e., one that could be generated by a Turing machine). Since computers only contained a finite number of instructions (or programs), one might argue, they could not reproduce human intelligence. Turing called this the ``mathematical objection' to his view that machines can think. Logico-mathematical reasons, stemming from his own work, helped to convince Turing that it should be possible to reproduce human intelligence, and eventually compete with it, by developing the appropriate kind of digital computer. He felt it should be possible to program a computer so that it could learn or discover new rules, overcoming the limitations imposed by the incompleteness and undecidability results in the same way that human mathematicians presumably do.