Social logics and expert systems

My goal is to emphasize the way we generally use the word logic and the sort of problems related to the definition of logic and the sort of problems related to the definition of logic. I also wish to underline the differences between human intelligence and artificial intelligence.I underline what, in my opinion, are the consequences for skill and knowledge transfer when using logic-based methodologies in landscapes deeply different from an input landscape. In this case I use, as a paradigm, the Indian way of logic, that has developed an original form of formal logic different from the Western logic.     

An introduction to expert systems

The paper considers the features of expert systems which make them of educational interest, and discusses issues of knowledge representation through rule sets, and how such systems can be used to give explanation and advice. Working systems are outlined in Medicine, Geology and Computing. Some limitations of expert systems are noted and their future potential assessed.     

Pragmatism and purism in artificial intelligence and legal reasoning

The paper identifies and assesses the implications of two approaches to the field of artificial intelligence and legal reasoning. The first — pragmatism — concentrates on the development of working systems to the exclusion of theoretical problems. The second — purism — focuses on the nature of the law and of intelligence with no regard for the delivery of commercially viable systems. Past work in AI and law is classified in terms of this division. By reference to The Latent Damage System, an operational system, the paper articulates and responds to conceivable purist (jurisprudential and AI) objections to such a program. The methods of the pragmatist are also called into question and refined. The author concludes that pragmatism within a purist framework is the only sound approach to developing reliable AI systems in law.     

基于集成式知识表示的专家系统开发工具

本文针对工程应用中知识的特点，提出了一种新型的知识表示方法－集成式的知识表示，给出了这种知识表示的ＢＮＦ范式，并就如何这诸多类型的知识正确、高效地推理进行了详细读者论坛，同时给出了推理过程的算法。     

Basic theoretical results for expert systems. Application to the supervision of adaptation transients in planar robots

The objective of expert systems is the use of Artificial Intelligence tools so as to solve problems within specific prefixed applications. In the last two decades a great experimental effort together with some theoretical knowledge have been employed to investigate the completeness and consistency of knowledge-based systems and to clarify the structure of these systems. Nevertheless, there is often a gap in the formalism which allows the structuring of the expert system programming towards the expert system design. In the last years, a new field called Ontological Engineering, defined by the IEEE as “the field that establishes a set of concepts, axioms, and relationships that describe a domain of scientific or technological interest” is trying to fill this gap. The work presented here may be placed in this context. In particular, the paper deals with the development of an expert system valid to optimize the adaptation transients arising in adaptive control using a logic formalism previously described, providing good simulation results. Its structure is composed by a supervisor based on an expert network organization and designed to improve the transient performances in the adaptive control of a planar robot. Apart form the basic adaptation scheme consisting of an estimation algorithm plus an adaptive controller, two additional coordinated expert systems are used to update an adaptation gain and the sampling period with a master expert system coordinating both above expert systems.     

Integrating medical expert systems, patient data-bases and user interfaces

Expert system applications in the clinical domain have not been very popular for lack of an adequate integration with other applications used in clinical environments. In the last few years, there is a growing trend towards the introduction of knowledge based systems as systems embedded in conventional applications. In this paper we propose an integration strategy of an expert system in oncology therapy with a clinical history data base and a user interface adapted to the needs of the medical environment. Our objective has been to design a system that is easy to use and provides all functions needed by the medical staff. The final system has consisted in first integrating three development tools and then using them in order to construct the complete application. The result is a global tool for the development of clinical information systems with embedded intelligent modules.     

Experts' systems instead of expert systems

By studying several cases of expert systems' use, a variety of difficulties were identified as directly depending on specific characteristics of experts and their tasks. This concerns more than the questions: “May experts be replaced by machines?” or “Is experts' knowledge explicable?”. The organisational structure of their work as well as the cyclic, non-plannable way of their task performing have further relevance. The paper introduces the concept of experts' systems to deal with diversities of their expertise and complexities of their work. It draws a distinction between non-monotonic problem solving, exploration, medium and modification, and argues that these modes are not reducible to yet another improved input/output strategy or dialogue style but introduce additional functions supporting the human-computer interaction according to experts' needs. In the first few sections, the paper covers the theoretical and empirical results of our research, whereas Section 4 introduces our design suggestions for experts' systems.     

Expert identification and selection: Legal liability concerns and directions

Legal liabilities pertaining to the identification and selection of domain experts is an issue that could adversely impact expert systems developers. Problems pertaining to flawed knowledge, improperly defined expertise, and behavioural and psychological impediments are just some of the issues. This paper examines the torts of strict products liability and negligence that system developers could incur as a result of expert-related difficulties. Parallels from legal scholars and federal and state court decisions are discussed relevant to expert system projects and developers. The paper concludes with a presentation of steps that systems developers can take to minimize potential legal liability.     

Use of ARIMA mathematical analysis to model the implementation of expert system courses by means of free software OpenSim and Sloodle platforms in virtual university campuses

This paper describes the implementation of a virtual World based in GNU OpenSimulator. This program offers a great variety of Web 3.0 ways of work, as it makes possible to visit web sites using avatars created for that purpose. The Universities should be familiar with the creation of new metaverses. That is the reason why a new basic methodology for the creation of a course on expert systems within a metaverse in a virtual campus for e-learning. Besides the creation of a repository or island, it is necessary to make measurements of the performance of the server dedicated to host the system when the number of users of the application grows. In order to forecast the behavior of such servers, ARIMA based time series are used. The auto-correlogrames obtained are analyzed to formulate a statistical model, as close to reality as possible.     

Intelligent systems in the automotive industry: applications and trends

There is a common misconception that the automobile industry is slow to adapt new technologies, such as artificial intelligence (AI) and soft computing. The reality is that many new technologies are deployed and brought to the public through the vehicles that they drive. This paper provides an overview and a sampling of many of the ways that the automotive industry has utilized AI, soft computing and other intelligent system technologies in such diverse domains like manufacturing, diagnostics, on-board systems, warranty analysis and design. Oleg Gusikhin received the Ph.D. degree from St. Petersburg Institute of Informatics and Automation of the Russian Academy of Sciences and the M.B.A. degree from the University of Michigan, Ann Arbor, MI. Since 1993, he has been with the Ford Motor Company, where he is a Technical Leader at the Ford Manufacturing and Vehicle Design Research Laboratory, and is engaged in different functional areas including information technology, advanced electronics manufacturing, and research and advanced engineering. He has also been involved in the design and implementation of intelligent control applications for manufacturing and vehicle systems. He is the recipient of the 2004 Henry Ford Technology Award. He holds two U.S. patents and has published over 30 articles in refereed journals and conference proceedings. He is an Associate Editor of the International Journal of Flexible Manufacturing Systems. He is also a Certified Fellow of the American Production and Inventory Control Society and a member of IEEE and SME. Nestor Rychtyckyj received the Ph.D. degree in computer science from Wayne State University, Detroit, MI. He is a technical expert in Artificial Intelligence at Ford Motor Company, Dearborn, MI, in Advanced and Manufacturing Engineering Systems. His current research interests include the application of knowledge-based systems for vehicle assembly process planning and scheduling. Currently, his responsibilities include the development of automotive ontologies, intelligent manufacturing systems, controlled languages, machine translation and corporate terminology management. He has published more than 30 papers in referred journals and conference proceedings. He is a member of AAAI, ACM and the IEEE Computer Society. Dimitar P. Filev received the Ph.D. degree in electrical engineering from the Czech Technical University, Prague, in 1979. He is a Senior Technical Leader, Intelligent Control and Information Systems with Ford Research and Advanced Engineering specializing in industrial intelligent systems and technologies for control, diagnostics and decision making. He is conducting research in systems theory and applications, modeling of complex systems, intelligent modeling and control, and has published 3 books and over 160 articles in refereed journals and conference proceedings. He holds 14 granted U.S. patents and numerous foreign patents in the area of industrial intelligent systems He is the recipient of the 1995 Award for Excellence of MCB University Press. He was awarded the Henry Ford Technology Award four times for development and implementation of advanced intelligent control technologies. He is an Associate Editor of International Journal of General Systems and International Journal of Approximate Reasoning. He is a member of the Board of Governors of the IEEE Systems, Man and Cybernetics Society and President of the North American Fuzzy Information Processing Society (NAFIPS).     

Rule-based expert systems to support step-by-step guidance in algebraic problem solving: The case of the tutor PAT2Math

In order for an Intelligent Tutoring System (ITS) to correct students’ exercises, it must know how to solve the same type of problems that students do and the related knowledge components. It can, thereby, compare the desirable solution with the student’s answer. This task can be accomplished by an expert system. However, it has some drawbacks, such as an exponential complexity time, which impairs the desirable real-time response. In this paper we describe the expert system (ES) module of an Algebra ITS, called PAT2Math. The ES is responsible for correcting student steps and modeling student knowledge components during equations problem solving. Another important function of this module is to demonstrate to students how to solve a problem. In this paper, we focus mainly on the implementation of this module as a rule-based expert system. We also describe how we reduced the complexity of this module from O(n^d) to O(d), where n is the number of rules in the knowledge base, by implementing some meta-rules that aim at inferring the operations students applied in order to produce a step. We evaluated our approach through a user study with forty-three seventh grade students. The students who interacted with our tool showed statistically higher scores on equation solving tests, after solving algebra exercises with PAT2Math during an approximately two-hour session, than students who solved the same exercises using only paper and pencil.     

Flexible control in expert systems for construction tasks

In most expert systems for constructional tasks, the knowledge base consists of a set of facts or object definitions and a set of rules. These rules contain knowledge about correct or ideal solutions as well as knowledge on how to control the construction process. In this paper, we present an approach that avoids this type of rules and thus the disadvantages caused by them.We propose a static knowledge base consisting of a set of object definitions interconnected by is-a and part-of links. This conceptual hierarchy declaratively defines a taxonomy of domain objects and the aggregation of components to composite objects. Thus, the conceptual hierarchy describes the set of all admissible solutions to a constructional problem. Interdependencies between objects are represented by constraints. A solution is a syntactically complete and correct instantiation of the conceptual hierarchy.No control knowledge is included in the conceptual hierarchy. Instead, the control mechanism will use the conceptual hierarchy as a guideline. Thus it is possible to determine in which respects a current partial solution is incomplete simply by syntactical comparison with the conceptual hierarchy. The control architecture proposed here has the following characteristics: separation of control and object knowledge, declarative representation of control knowledge, and explicit control decisions in the problem solving process. Thus, a flexible control mechanism can be realized that supports interactive construction, integration of case-based approaches and simulation methods.This control method is part of an expert system kernel for planning and configuration tasks in technical domains. This kernel has been developed at the University of Hamburg and is currently applied to several domains.     

Intelligent agent systems for manufacturing applications

Using the concept of intelligent agents, two system approaches are described for manufacturing applications. The first is based on the rule-based object (RBO) which is associated with a production-rules knowledge base and is implementable in an object-oriented development environment such as Smalltalk-80. A proof-of-concept automated guided vehicle (AGV) system of this kind has been recently developed. The second and more advanced approach is based on the intelligent agent object (IAO) and an AGV system of this kind is currently under development. This uses a multi-agent entity termed the modulon to handle more effectively both the co-operative planning task and the local route planning task.     

Cooperation between expert knowledge and data mining discovered knowledge: Lessons learned

Expert systems are built from knowledge traditionally elicited from the human expert. It is precisely knowledge elicitation from the expert that is the bottleneck in expert system construction. On the other hand, a data mining system, which automatically extracts knowledge, needs expert guidance on the successive decisions to be made in each of the system phases. In this context, expert knowledge and data mining discovered knowledge can cooperate, maximizing their individual capabilities: data mining discovered knowledge can be used as a complementary source of knowledge for the expert system, whereas expert knowledge can be used to guide the data mining process. This article summarizes different examples of systems where there is cooperation between expert knowledge and data mining discovered knowledge and reports our experience of such cooperation gathered from a medical diagnosis project called Intelligent Interpretation of Isokinetics Data, which we developed. From that experience, a series of lessons were learned throughout project development. Some of these lessons are generally applicable and others pertain exclusively to certain project types.     

控讨基于教学过程的ITS系统模型

计算机智能导师系统（ＩＴＳ）,是智能化教学的一个分支。围绕教师在常规教学过程中所起的作用,分析研究了教师在教学的各个阶段中所承担的角色和完成的工作,并根据教学过程的动态特性,提出了一个基于教学过程的ＩＴＳ模型。还针对ＩＴＳ模型中的学科知识库、学生模型和教学策略推理机的实现方法给出了描述。     

A survey of reasoning procedures in knowledge based systems for economics and management

This paper surveys reasoning and inference strategies as especially relevant for knowledge based systems in economics and management. This requires elements of object oriented features, numerical and text constraints, search over time, game power conflict resolution. Specific functionalities are discussed.     

A prolog based expert system for the allocation of quality assurance program resources

The worldwide proliferation of fraudulent materials has brought about the need for a new approach to the control of purchased material quality. Nuclear power, defense, aerospace and many other industries are affected by the supply of poor quality clones that presume to be original replacement parts. Safety considerations abound as these highly defective materials are used in systems that are critical to the preservation of human lives. Commonly utilized quality assurance programs have not effectively stopped the influx of fraudulent materials. These programs fail to concentrate inspection efforts on materials and inspection attributes that would effectively prevent the acceptance of fraudulent materials. herein a solution is presented to this problem in the form of an expert system application. Information commonly available in industry is formulated into a knowledge based system wherein advisories are given to the user regarding key purchased material receipt inspection strategies.     

Testability of expert systems in system development and application

In this paper the difficulties arising out of a necessary examination of expert systems as to the ‘correctness’ of functioning are outlined. The argumentation is based on the problematic use of the knowledge term in expert system development and the design perspectives connected with the cognitivistic knowledge concept. It becomes obvious that fundamental problems in system development will involve negative consequences for utilization. The perspective developed from this analysis is assuming that these problems have to be taken into account in development and have to be elucidated for utilization.