Revising threshold functions

A revision algorithm is a learning algorithm that identifies the target concept, starting from an initial concept. Such an algorithm is considered efficient if its complexity (in terms of the resource one is interested in) is polynomial in the syntactic distance between the initial and the target concept, but only polylogarithmic in the number of variables in the universe. We give an efficient revision algorithm in the model of learning with equivalence and membership queries for threshold functions, and some negative results showing, for instance, that threshold functions cannot be revised efficiently from either type of query alone. The algorithms work in a general revision model where both deletion and addition type revision operators are allowed.     

Interactive simulated patient—an advanced tool for student-activated learning in medicine and healthcare

An advanced learning system for interactive simulation of patient cases (ISP) is described. The system was designed to meet specific pedagogical needs where student activation and problem orientation were two of the key issues. The system includes features such as video based illness history-taking function using free text input, highly interactive physiological examination procedures, extensive laboratory tests and detailed user feedback. The system was constructed mainly in Authorware Professional, starting more than 10 years ago, and it is now available in refined versions in different languages. Twelve pedagogical and three technical features were initially defined for the project. All of these aims were fulfilled. The ISP system has been successfully used in education, and in international collaboration, including three applicability field tests. The system is also a powerful research tool for studying for instance medical decision-making.     

Context-gated knowledge partitioning in categorization.

According to the knowledge partitioning framework, people sometimes master complex tasks by creating multiple independent parcels of partial knowledge. Research has shown that knowledge parcels may contain mutually contradictory information, and that each parcel may be used without regard to knowledge that is demonstrably present in other parcels. This article reports 4 experiments that investigated knowledge partitioning in categorization. When component boundaries of a complex categorization were identified by a context cue, a significant proportion of participants learned partial and independent categorization strategies that were chosen on the basis of context. For those participants, a strategy used in one context was unaffected by knowledge demonstrably present in other contexts, suggesting that knowledge partitioning in categorization can be complete. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

神经网络系统学习过程初探

本文给出了神经网络系统学习过程的一个随机模型--马尔柯夫模型,从最大熵原理的 观点讨论神经网络系统的学习过程,提出将神经网络系统的学习过程分为两个阶段的想法并 给出学习过程的算法.     

用网络计划技术优化企业生产计划问题

应用网络计划技术对杭州开关厂在生产计划控制中存在的实际问题进行了深入的研究。在充分剖析理论的基础上，结合实际工作情况，对大型机电一体化设备CTH500kW中频加热机的生产技术准备工作进行了网络计划的编制。其中有工程分解的“条块”结合、工序编码系统、资源优化与时间优化的兼容等，取得了良好的成果。     

Visual thinking in arts education: Homage to Rudolf Arnheim.

The influence of Arnheim's work on the author's research began with an experiment on the perception of visual balance. Two later research projects emerged from the profound influence of Arnheim's stance toward creation in the visual arts as a serious, cognitive endeavor. A series of meta-analyses were first conducted to test the claim that learning in the arts transfers to nonarts cognitive domains, but little evidence was found. Past research on the transfer hypothesis was found to be lacking because of its failure to assess learning in the parent domain. Therefore, a new research project was carried out to identify kinds of learning in the parent domain of visual arts. We identified eight thinking dispositions developed in serious visual arts classes, setting the stage for more plausible transfer studies. This study demonstrates that the visual arts inculcate basic skills in perception and cognition that exist both in the arts and sciences. All of the skills the authors describe can, with some modification, be transferred to the science laboratory. As Rudolf Arnheim has taught us, visual thinking is everywhere. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Confucian and Socratic learning.

Replies to the comments by R. A. R. Gurung (see record 2003-03405-011) and J. Li (see record 2003-03405-012) regarding comments on the article by R. G. Tweed and D. R. Lehman (2001) which stated that a Confucian-Socratic framework provides a structure for analyzing culture-influenced aspects of academic learning. In this article, Tweed and Lehman argued that these ancient exemplars model approaches to learning continue to differentiate students within a modern Canadian postsecondary context. In this reply, Tweed and Lehman advise caution in how Gurung placed their Confucian-Socratic framework within the context of prior theory on education and epistemological development because these models were developed exclusively in the West. Furthermore, Tweed and Lehman believe that Li's argument misinterpreted their article, and that they should of consistently used the term "personal reform" rather than "behavioral reform" in order to communicate the depth of personal change envisioned by Confucius. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

What do we learn from binding features? Evidence for multilevel feature integration.

Four experiments were conducted to investigate the relationship between the binding of visual features (as measured by their aftereffects on subsequent binding) and the learning of feature-conjunction probabilities. Both binding and learning effects were obtained, but they did not interact. Interestingly, (shape-color) binding effects disappeared with increasing practice, presumably because of the fact that only 1 of the features involved was relevant to the task. However, this instability was only observed for arbitrary, not highly overlearned combinations of simple geometric features and not for real objects (colored pictures of a banana and strawberry), where binding effects were strong and resistant to practice. These findings suggest that learning has no direct impact on the strength or resistance of bindings or on speed with which features are bound; however, learning does affect the amount of attention particular feature dimensions attract, which again can influence which features are considered in binding. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

最优特征子集选择问题

机器学习和模式识别面临的一个重要问题，就是特征子集的选择问题，即从一个大的已生征特集合，选择一个子集合来一致地描述已知例。特别，最优特征子集选择问题，即最小的特征子集问题的 计算杂性至今学不清楚。     

The Design of Discrimination Experiments

Experimentation plays a fundamental role in scientific discovery. Scientists experiment to gather data, investigate phenomena, measure quantities, and test theories. In this article, we address the problem of designing experiments to discriminate between two completing theories. Given an initial situation for which the two theories make the same prediction, the experiment design problem is to determine how to modify the situation such that the two theories make different predictions for the modified situation. The modified situation is called a discrimination experiment. We present a knowledge-intensive method called DEED for designing discrimination experiments. The method analyzes the differences in the two theories' explanations of the prediction for the initial situation. Based on this analysis, it determines modifications to the initial situation that will result in a discrimination experiment. We illustrate the method with the design of experiments to discriminate between several pairs of qualitative theories in the fluids domain.