Markov analysis of qualitative dynamics1

Common sense sometimes predicts events to be likely or unlikely rather than merely possible. We extend methods of qualitative reasoning to predict the relative likelihoods of possible qualitative behaviors by viewing the dynamics of a system as a Markov chain over its transition graph. This involves adding qualitative or quantitative estimates of transition probabilities to each of the transitions and applying the standard theory of Markov chains to distinguish persistent states from transient states and to calculate recurrence times, settling times, and probabilities for ending up in each state. Much of the analysis depends solely on qualitative estimates of transition probabilities, which follow directly from theoretical considerations and which lead to qualitative predictions about entire classes of systems. Quantitative estimates for specific systems are derived empirically and lead to qualitative and quantitative conclusions, most of which are insensitive to small perturbations in the estimated transition probabilities. The algorithms are straightforward and efficient.     

Intelligent handling of data by integration of commonsense reasoning

Any intelligent problem solving system should be able, given the known data on a case, to decide whether some item of information is true, false or unknown. In this paper the way in which various forms of commonsense reasoning can be integrated to provide such decisions is described. To this end three structural types of knowledge defined over data, and four strategies for exploiting these structures, are identified. ‘Decide-Status’ integrates the reasoning strategies into a task frame. This frame structure not only integrates the reasoning but also affords the appropriate facilities for providing strategic justifications for its conclusions, if required.     

CO2 emissions,energy consumption,and output in France

This paper examines the dynamic causal relationships between pollutant emissions, energy consumption, and output for France using cointegration and vector error-correction modelling techniques. We argue that these variables are strongly inter-related and therefore their relationship must be examined using an integrated framework. The results provide evidence for the existence of a fairly robust long-run relationship between these variables for the period 1960–2000. The causality results support the argument that economic growth exerts a causal influence on growth of energy use and growth of pollution in the long run. The results also point to a uni-directional causality running from growth of energy use to output growth in the short run.     

Casual reasoning in planning1

Reasoning about actions necessarily involves tracking the truth of assertions about the world over time. The SIPE planning system retains the efficiency of the STRIPS assumption for this while enhancing expressive power by allowing the specification of a causl theory. Separation of knowledge about causality from knowledge about actions relieves operators of much of their representational burden and allows them to be applicable in a wide range of contexts. The implementation of causal theories is described, together with examples and evaluations of the system's expressive power and efficiency.     

Notes on Ginsberg's multivalued logics

The use of multivalued logics for knowledge representation and nonmonotonic reasoning has often been advocated, in particular within the general framework proposed by Ginsberg in his paper "Multivalued logics: a uniform approach to reasoning in artificial intelligence." His system is based on a multivalued logic with an arbitrary number of truth values classified with respect to two partial orders, a truth order and a knowledge order. This classification is very interesting and gives an intuitive appeal to the framework. In this paper the work by Ginsberg is critically reviewed, pointing out some flaws and ways to overcome them. Moreover, we present some ideas on how to modify the original schema in order to obtain a more semantically well-founded framework.
L'utilisation de la Iogique multivalente pour la représentation des connaissances et le raisonnement non monotone a souvent été préconisée, en particulier à l'intérieur du cadre général proposé par Ginsberg dans son article intitulé〘 Multivalued logics: a uniform approach to reasoning in artificial intelligence 〙 Son système est basé sur une logique multivalente comportant un nombre arbitraire de valeurs de vérité classées selon deux ordres partiels: un ordre de vérité et un ordre de connaissances. Cette classification est très intéressante et donne un attrait intuitif au cadre. Dans cet article, l'auteur examine le travail de Ginsberg, y relève des lacunes et propose des moyens de les corriger. De plus, il expose certaines idées en vue de modifier le schéma original et ainsi obtenir un meilleur cadre du point de vue de la sémantique.     

Temporal aggregation and spurious instantaneous causality in multiple time series models

Large aggregation interval asymptotics are used to investigate the relation between Granger causality in disaggregated vector autoregressions (VARs) and associated contemporaneous correlation among innovations of the aggregated system. One of our main contributions is that we outline various conditions under which the informational content of error covariance matrices yields insight into the causal structure of the VAR. Monte Carlo results suggest that our asymptotic findings are applicable even when the aggregation interval is small, as long as the time series are not characterized by high levels of persistence.     

格兰杰因果关系检验模型分析与应用

目的 分析格兰杰因果关系检验模型,应用格兰杰因果检验模型检验房地产市场中的地价与房价之间的因果关系.方法 修正了沈阳市地价与房价的环比价格指数,对沈阳市地价与房价之间的关系进行平稳性检验,协整检验和格兰杰因果检验.结果 沈阳市房价是地价的格兰杰原因,房价的上涨会带动地价的上涨;而地价不是房价的格兰杰原因,但地价作为房价的重要组成部分,对房价有一定的影响作用.土地只是构成房地产的一个生产要素,其需求的变化是受房屋市场需求变化影响的,房屋市场供不应求,价格上涨,才使开发商对土地的需求增加,造成地价上涨.结论 土地招标、拍卖和挂牌政策的实施不是造成房价上涨的主要原因.     

湖南省能源消费与经济增长均衡关系实证分析

利用湖南省1999—2008年的经济与能源数据,在对湖南省经济总量、能源消费总量、能源消费构成以及单位GDP能耗等现状分析的基础上,采用ADF检验法、Granger因果关系检验法等计量方法研究了湖南省能源消费与经济增长之间的关系。实证研究表明:湖南省能源消费与经济增长之间存在长期均衡关系,并且存在从经济增长到能源消费的单向Granger因果关系。     

陕西对外贸易与经济增长关系的协整分析

以陕西省作为研究对象,根据陕西省1980—2007年的数据,利用Granger因果关系检验、协整分析和误差修正模型分析陕西省对外贸易和经济增长的关系,结果表明,陕西省对外贸易和经济增长存在长期的协整关系;陕西属于出口导向型经济,出口是经济增长的Granger原因,进口不是经济增长的Granger原因,却是出口增长的Grange原因,由此说明,进口对经济增长有间接的作用。     

基于干预规则挖掘因果关系与分段干预事件及对比不等式

为揭示亚复杂系统(SCS)在干预下的特殊行为,提出了对比不等式概念,提出并实现了分段干预规则的挖掘算法;通过在亚复杂系统中施加扰动式干预并分析其动力学效应,提出并实现了基于扰动因果关系挖掘算法。在真实数据上的实验表明,分段干预规则发现了传统挖掘方法难以发现的新干预事件,因果挖掘算法发现了传统方法难以发现的因果关系。