Artificial Intelligence and the Management Science Practitioner: One Definition of Knowledge-Based Expert Systems

1989 ◽  
Vol 19 (5) ◽  
pp. 66-70 ◽  
Author(s):  
Kenneth Fordyce ◽  
Peter Norden ◽  
Gerald Sullivan
Keyword(s):  
Artificial Intelligence ◽  
Expert Systems ◽  
Management Science ◽  
Knowledge Based ◽  
Definition Of

On techniques of expert systems on the example of the Akinator program

2020 ◽  
Vol 25 (2) ◽  
pp. 7-13
Author(s):  
Zhangozha A.R. ◽  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Neural Networks ◽  
Expert Systems ◽  
Knowledge Base ◽  
Hybrid Systems ◽  
Online Game ◽  
Basic Principles ◽  
The Moment ◽  
Definition Of

On the example of the online game Akinator, the basic principles on which programs of this type are built are considered. Effective technics have been proposed by which artificial intelligence systems can build logical inferences that allow to identify an unknown subject from its description (predicate). To confirm the considered hypotheses, the terminological analysis of definition of the program "Akinator" offered by the author is carried out. Starting from the assumptions given by the author's definition, the article complements their definitions presented by other researchers and analyzes their constituent theses. Finally, some proposals are made for the next steps in improving the program. The Akinator program, at one time, became one of the most famous online games using artificial intelligence. And although this was not directly stated, it was clear to the experts in the field of artificial intelligence that the program uses the techniques of expert systems and is built on inference rules. At the moment, expert systems have lost their positions in comparison with the direction of neural networks in the field of artificial intelligence, however, in the case considered in the article, we are talking about techniques using both directions – hybrid systems. Games for filling semantics interact with the user, expanding their semantic base (knowledge base) and use certain strategies to achieve the best result. The playful form of such semantics filling programs is beneficial for researchers by involving a large number of players. The article examines the techniques used by the Akinator program, and also suggests possible modifications to it in the future. This study, first of all, focuses on how the knowledge base of the Akinator program is built, it consists of incomplete sets, which can be filled and adjusted as a result of further iterations of the program launches. It is important to note our assumption that the order of questions used by the program during the game plays a key role, because it determines its strategy. It was identified that the program is guided by the principles of nonmonotonic logic – the assumptions constructed by the program are not final and can be rejected by it during the game. The three main approaches to acquisite semantics proposed by Jakub Šimko and Mária Bieliková are considered, namely, expert work, crowdsourcing and machine learning. Paying attention to machine learning, the Akinator program using machine learning to build an effective strategy in the game presents a class of hybrid systems that combine the principles of two main areas in artificial intelligence programs – expert systems and neural networks.

Expert Systems in Distance Education

2018 ◽  
pp. 1410-1423
Author(s):  
Duygu Mutlu-Bayraktar ◽  
Esad Esgin
Keyword(s):  
Artificial Intelligence ◽  
Distance Education ◽  
Natural Language ◽  
Expert Systems ◽  
Expert Knowledge ◽  
Computer Systems ◽  
Educational Environments ◽  
Artificial Environment ◽  
Present Solution ◽  
Definition Of

Computers have been used in educational environments to carry out applications that need expertise, such as compiling, storing, presentation, and evaluation of information. In some teaching environments that need expert knowledge, capturing and imitating the knowledge of the expert in an artificial environment and utilizing computer systems that have the ability to communicate with people using natural language might reduce the need for the expert and provide fast results. Expert systems are a study area of artificial intelligence and can be defined as computer systems that can approach a problem for which an answer is being sought like an expert and present solution recommendations. In this chapter, the definition of expert systems and their characteristics, information about the expert systems in teaching environments, and especially their utilization in distance education are given.

A survey of French developments in knowledge-based systems

1987 ◽  
Vol 2 (4) ◽  
pp. 287-295
Author(s):  
Jean-Claude Rault
Keyword(s):  
Artificial Intelligence ◽  
Expert Systems ◽  
Computer Applications ◽  
Computer Architectures ◽  
Software Components ◽  
Industrialized Countries ◽  
Public Announcement ◽  
Knowledge Based ◽  
Fifth Generation ◽  
Industrial Communications

AbstractLike other industrialized countries, France is currently enjoying a vogue for artificial intelligence and, generally, for hardware and software components and structures which will be needed for the design and implementation of the computer applications of the 1990s.Since public announcement of MITI's Fifth Generation Project in October 1981, the French scientific and industrial communications have exhibited increasing enthusiasm for AI languages, expert systems, man-computer interaction, novel computer architectures, and knowledge-based computer systems as a whole. The choice of the Prolog language for the Japanese project has stimulated many French industrialists to be aware of the existence of a basic AI tool designed mainly in France.In spite of the present fashion, often maintained by the journalistic milieu, it would be inaccurate to say that the French fifth generation project goes back to the Japanese announcement. The MITI project has certainly been a catalyst of ministerial and industrial awareness, but the bulk of ongoing projects stem from earlier work most often funded by government agencies.In spite of the current thrust in AI and the centralizing habit in France, a “flagship” AI project cannot be identified. French Research and Development initiatives in artificial intelligence in general, and expert systems in particular, correspond more to a set of distinct projects. These frequently complement each other in technical scope and in their scientific and industrial objectives.

USING EXPERT SYSTEMS FOR IMAGE UNDERSTANDING

1987 ◽  
Vol 01 (02) ◽  
pp. 237-250 ◽  
Author(s):  
P. SUETENS ◽  
A. OOSTERLINCK
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Expert Systems ◽  
Review Paper ◽  
Image Understanding ◽  
Interested Reader ◽  
Knowledge Based ◽  
Survey Papers ◽  
Application Fields

Expert systems and image understanding have traditionally been considered as two separate application fields of artificial intelligence (AI). In this paper it is shown, however, that the idea of building an expert system for image understanding may be fruitful. Although this paper may serve as a framework for situating existing works on knowledge-based vision, it is not a review paper. The interested reader will therefore be referred to some recommended survey papers in the literature.

Legal Aspects of Knowledge-Based Technology

1988 ◽  
Vol 3 (1) ◽  
pp. 9-16
Author(s):  
Roger Clarke
Keyword(s):  
Expert Systems ◽  
Legal Aspects ◽  
Policy Implications ◽  
Commercial Exploitation ◽  
Knowledge Based ◽  
Legal Difficulties ◽  
Definition Of ◽  
Ownership Rights

A definition of knowledge-based technology (KBT) is provided which is more operational than conventional definitions of the term ‘expert systems’. Ownership rights in products developed using KBT are considered and difficulties discussed. Legal liabilities which may arise from such products are considered and issues identified. It is concluded that commercial exploitation of KBT may be hindered by these legal difficulties. Some policy implications are identified.

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