人工智能在决策支持系统中的应用与研究

本文首先介绍了决策支持系统(DSS)的定义，针对其局限性提出了人工智能(AI)与决策支持系统的结合，然后分述了专家系统(ES)，机器学习(RL)，及智能体(Agent)在决策支持系统中的应用与研究。     

人工智能的应用研究

本文对人工智能的发展过程及现在研究的热点进行了简要的概述,重点对人工智能的应用研究领域做了阐述。     

人工智能技术在计算机辅助教学中的应用

介绍了计算机辅助教学系统及其现状,提出了智能计算机辅助教学系统(ICAI)的未来发展前景.     

基于人工智能的机电设备智能保障系统研究

为解决现代机电设备的运行管理、状态监测、故障快速诊断与维修以及保障决策问题,借鉴人工智能的先进研究成果,构建了机电设备智能保障系统.介绍了系统的组成和实现的功能,对系统知识库、模型库和数据库设计中的关键技术进行了分析,应用神经网络技术实现多种推理,提高了故障诊断效率,采用计算机网络通讯技术,实现了系统的远程智能决策和技术指导,实践证明,该系统安全可靠,实用价值较高.     

人工智能的挑战

人工智能（Artificial Intelligence)作为当前科学技术发展中的一门前沿学科，面临很多争论、困难和挑战，本文从两大方面论述了人工智能面临的机遇和挑战。     

人工智能在电路故障诊断中的应用

本文主要介绍人工智能在电路故障诊断中的应用,提出电路故障诊断专家系统的概念、模型及发展前景。     

人工智能技术在计算机辅助教学中的应用与实现

介绍了计算机辅助教学系统及其现状,分析了现代教育技术与传统教育模式的各自特点,探讨了ICAI的实现原理及利用ICAI对教学的改进方案,并对智能计算机辅助教学系统进行了详细讨论,最后说明了将计算机技术、人工智能技术与网络技术应用于教学过程的必然性、必要性和有效性。     

人工智能控制研究与应用的几个时期及展望

从历史角度,较全面地论述了人工智能这门交叉学科的研究与应用的各个发展时期及展望,对于我们了解这门学科的发展经过以及进一步深入研究智能控制及应用有一定的参考价值。     

人工智能技术在教育中的应用

人工智能技术作为各种学科相互渗透的产物,其理论和应用的研究领域几乎涉及人类的一切活动范畴,本文主要介绍人工智能在教育中的应用,特别针对人工智能技术应用在教育中产生的智能化计算机辅助教学系统进行了详细讨论.     

ITS系统中自然语言人机接口的设计与实现

文中详细介绍了智能教学系统ＭＳＣＩＴＳ中基于知识的自然语言人机接口的设计及实现方法。     

Algorithm recognition for programming tutoring based on flow graph parsing

Plan-recognition with template matching shows reasonable performance for recognizing general control structures. However, problems containing well-defined algorithms such as sorting and searching are difficult to recognize by the template-based methodology alone, because an algorithm is often highly optimized and therefore hard to divide into smaller meaningful units. Based on this observation, we propose an algorithm recognition methodology to augment the plan-recognition approach.Our algorithm recognition approach is based on the flow graph parsing which performs a partial recognition of programs. The methodology is extended to completely understand algorithm implementations by providing the information of the program's goal, a specification of programming assignment in tutoring environment. Utilization of goal information is two-fold; extending the role of transformation rules to represent algorithm-specific information and looking for salient graph parts of algorithm plan to determine which has been used to implement the goal. Preliminary evaluation was performed on students' programs containing sort algorithm.     

一种基于模糊Petri网的不确定知识获取方法及其应用

本文介绍一种基于模糊Petri网获取专家系统不确定知识的方法,文中给出了模糊Petri网的知识表示、不确定推理算法及应用实例。     

MODELS OF HUMAN COMMUNICATION: DIALOGUE WITH COMPUTER

A model of understanding texts of a natural language is presented, which consists of three levels. On the first level, the system uses only information in the given text. On the second level, it employs additional information from a knowledge base. On the third level, understanding is connected with some activity of the system stimulated by the available information.     

An intelligent computer-assistant for stylistic instruction

This article describes an intelligent computer-assisted language instruction system that is designed to teach principles of syntactic style to students of English. Unlike conventional style checkers, the system performs a complete syntactic analysis of its input, and takes the student's stylistic intent into account when providing a diagnosis. Named STASEL for Stylistic Treatment At the Sentence Level, the system is specifically developed for the teaching of style, and makes use of artificial intelligence techniques in natural language processing to analyze free-form input sentences interactively.An important contribution of STASEL is its ability to provide stylistic guidance according to the specific writing goals of clarity and conciseness. In an attempt to remedy some of the deficiencies of existing instructional software, STASEL's design demonstrates how stylistic instruction can be effectively computerized, while laying the groundwork for the creation of intelligent tutoring systems for teaching writing.Graeme Hirst is an associate professor of computer science at the University of Toronto. He is the author of Semantic Interpretation and the Resolution of Ambiguity (Cambridge, 1987), and many papers on natural language understanding.Julie Payette received her B.Eng. in electrical engineering from McGill University (1986) and her M.A.Sc. from the University of Toronto (1990). She has recently been selected as a Canadian astronaut, and is currently training at the Canadian Space Agency in Ottawa.     

Knowledge-support systems

The social role of information technology is analysed in order to provide a framework for reasonable requirements for knowledge support systems. The many different scientific and engineering communities targeted on the development of specific knowledge support technologies are noted, and the problems of integrating developments from different communities are highlighted. The architectures of current integrated knowledge support systems are analysed within the social framework and the strengths and weaknesses of current modules are evaluated. Major system developments in recent years are used to exemplify the analysis, and expected directions for future development are outlined. The framework, analyses and examples are used to define a structured requirements specification for future research and development related to knowledge support systems.     

Automatic estimation of exercises' difficulty levels in a tutoring system for teaching the conversion of natural language into first‐order logic

The estimation of the difficulty level of exercises is a fundamental aspect of intelligent tutoring systems, and it is necessary in order to achieve better adaptation to the students' needs and maximize learning efficiency. In this article, we present an approach to automatically estimates the difficulty level of exercises in natural language (NL) to first‐order of logic (FOL). The estimation of an exercise's difficulty level is based on the complexity of the corresponding answer, that is the FOL formula, as well as the structure and the semantics of the exercise, that is a natural language sentence and it is carried out in two main steps. Initially, a preliminary estimation is performed based on the complexity of the FOL formula. The system takes as input parameters the number, the type and the order of quantifiers, the number of implications, and the number of different connectives. Afterwards, the final estimation is made based on both semantic aspects of the NL sentence and the structure of the FOL formula. An evaluation study was conducted to assess the system's performance, and the results are very encouraging.     

A predictive approach for the generation of rhetorical devices

Human discourse is fraught with rhetorical devices such as contradictions, illustrations, and analogies. These rhetorical devices carry important information which a listener uses to speed up the comprehension process. In this paper, we present a taxonomy of rhetorical devices commonly used in tutoring environment, and model the meaning of a class of rhetorical devices in terms of their anticipated effect on a listener's knowledge. These predictions are then used in planning computer-generated discourse. As a testbed for our ideas, a system called WISHFUL is being implemented to generate commentaries in the domain of high-school algebra within the framework of an intelligent tutoring system.     

石油价格预测专家系统OPFES的设计与实现

本文以国际市场石油价格预测问题为背景,采用了大型专家系统设计方法,论述了一个石油价格预测专家系统 OPFES(Oil Price Forecast Expert System)的设计方法.在系统中采用了广义知识表达树作为知识表达方法,系统结构上采用了四库结构(模型库、方法库、数据库、知识库).在推理机方面采用了二级推理:元知识级推理与对象级推理的灵活方式.在人机接口方面,采用了多级菜单驱动方式与有限的自然语言理解方式.整个系统的原型系统用 Turbo-Prolog 语言已在 PC/AT 机上实现.