Information-Based Evaluation Criterion for Classifier's Performance

In the past few years many systems for learning decision rules from examples were developed. As different systems allow different types of answers when classifying new instances, it is difficult to appropriately evaluate the systems' classification power in comparison with other classification systems or in comparison with human experts. Classification accuracy is usually used as a measure of classification performance. This measure is, however, known to have several defects. A fair evaluation criterion should exclude the influence of the class probabilities which may enable a completely uninformed classifier to trivially achieve high classification accuracy. In this paper a method for evaluating the information score of a classifier's answers is proposed. It excludes the influence of prior probabilities, deals with various types of imperfect or probabilistic answers and can be used also for comparing the performance in different domains.     

Self-learning inductive inference machines

Self-knowledge is a concept that is present in several philosophies. In this article, we consider the issue of whether or not a learning algorithm can in some sense possess self-knowledge. The question is answered affirmatively. Self-learning inductive inference algorithms are taken to be those that learn programs for their own algorithms, in addition to other functions.
La connaissance de soi est un concept qui se retrouve dans plusieurs philosophies. Dans cet article, les auteurs s'interrogent à savoir si un algorithme d' apprentissage peut dans une certaine mesure posséder la connaissance de soi. lis apportent une reponse positive a cette question. Les algorithmes d'inference inductive autodidactes sont ceux qui font l'apprentissage de programmes pour leurs propres algorithmes, en plus d' autres fonctions.     

钻机绞车滚筒体的窄间隙埋弧焊

针对钻机绞车滚筒体采用手工电弧焊工人劳动强度大、焊接效率低、质量不稳定及返修率高等问题,研制了钻机绞车滚筒体窄间隙埋弧焊专机。该专机由ESAB—A2埋弧焊电源和焊接小车、窄间隙焊头、滚轮架、防窜装置、旋转地线夹、三维焊接工作台、焊剂自动回收机组成。使用表明,采用该焊机焊接的滚筒体焊缝质量完全符合设计要求,合格率100%,焊接效率比原来提高6倍。每件滚筒体的焊接可降低人工成本约80%。     

Evaluating the design of flexible manufacturing systems

Evaluating the design of flexible manufacturing systems is complex. Developing a measure of performance useful for evaluating alternate designs continues to be interesting. Here, total productivity of the system is proposed as an appropriate measure. Specification of parameters based upon strategic considerations for this measure are discussed. Finally, the usefulness of the measure is demonstrated through an example.     

PAC-learnability of probabilistic deterministic finite state automata in terms of variation distance

We consider the problem of PAC-learning distributions over strings, represented by probabilistic deterministic finite automata (PDFAs). PDFAs are a probabilistic model for the generation of strings of symbols, that have been used in the context of speech and handwriting recognition, and bioinformatics. Recent work on learning PDFAs from random examples has used the KL-divergence as the error measure; here we use the variation distance. We build on recent work by Clark and Thollard, and show that the use of the variation distance allows simplifications to be made to the algorithms, and also a strengthening of the results; in particular that using the variation distance, we obtain polynomial sample size bounds that are independent of the expected length of strings.     

Multiagent learning using a variable learning rate

Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on the policies of the other agents. This creates a situation of learning a moving target. Previous learning algorithms have one of two shortcomings depending on their approach. They either converge to a policy that may not be optimal against the specific opponents' policies, or they may not converge at all. In this article we examine this learning problem in the framework of stochastic games. We look at a number of previous learning algorithms showing how they fail at one of the above criteria. We then contribute a new reinforcement learning technique using a variable learning rate to overcome these shortcomings. Specifically, we introduce the WoLF principle, “Win or Learn Fast”, for varying the learning rate. We examine this technique theoretically, proving convergence in self-play on a restricted class of iterated matrix games. We also present empirical results on a variety of more general stochastic games, in situations of self-play and otherwise, demonstrating the wide applicability of this method.     

基于约束优化的联想记忆模型学习算法

本文提出了一种对称互连神经元网络的学习策略,利用全局约束优化方法确定连接权。优化过程采用了梯度下降技术。这种学习算法可以保证训练样本成为系统的稳定吸引子,并且具有优化意义上的最大吸引域。本文讨论了网络的存储容量,训练样本的渐近稳定性和吸引域大小。计算机实验结果说明了学习算法的优越性。     

Conceptual design of a high-efficiency absorption cooling cycle

The search for high-efficiency, gas-fired cooling cycles has led to the development of dual-loop absorption machines with cooling coefficients of performance (COPs) in the 1.2 to 1.7 range. This increased performance may call for high generator temperatures, new working fluids or new materials of construction. In most cases, two different sets of working fluids are required. The conceptual design presented here is aimed at obtaining high efficiencies with relatively low temperatures, employing only one set of fluids. The concept consists of two loops coupled in a configuration aimed at minimizing the loss of thermodynamic availability incurred when transferring refrigerant between the loops. The working fluid pair is a solution of lithium bromide-water. The calculated COPs are of the order of 1.8. The cycle relies on an elaborate evaporator-absorber combination. The paper presents the conceptual design, the critical assumptions, and the performance calculations for the concept.     

CETRAN系统中的英语词汇结构与功能

本文介绍了汉英机器翻译系统中从中间媒介语言生成英语的生成系统的词汇结构和功能，描述了生成系统各个层次之间的转换原理。为了说明清楚，在叙述中注意了列举从中间媒介中间媒介语言到目标语句的生成实例。