User:Heron10/sandbox
Expert systems were among the first forms of artificial intelligence (AI) software. The systems attempted to capture the expertise of specialists to make the knowledge available to others. Initially, this methodology was not available to the general public because of mainframe computer costs and complex programming requirements. A variety of expert system building tools for personal computers were developed in the 1980's that made this methodology available outside of universities and large corporations. VP-Expert was one of these systems.
Origins
VP-Expert was first published by Paperback Software International in 1984 and upgraded in 1985 and 1987.[1] In June 1991, ownership of VP-Expert was transferred to WordTech Systems, Inc. in 1991 after Paperback Software was liquidated. In 1992 Wordtech supported an upgrade to version 3.0. VP-Expert was widely used in the 1980’s, but usage declined in the early 1990’s.
The expert system shell was written in the C programming language. It was created and upgraded by Brian Sawyer,[1] author of Programming Expert Systems in Pascal[2]
Features
VP-Expert[3][4] [5] is a rule-based expert system in which the knowledge engineer enters if-then rules. A knowledge base was developed, a collection of rules pertaining to the expertise of an area of knowledge. Induction was more direct means of entering the expertise, using a set of examples and observations by the user.[6] Currently, data mining is used to discover new knowledge in data unknown to the expert. Once the expert system was built, the expertise could be ported to end users using the IBM-PC. Current expert systems can be developed and ported to machines from personal computers to supercomputers.<clips ref> VP-Expert could receive input from spreadsheets and database software. Rules could be backward chaining or forward chaining. VP-Expert includes hypertext, support for mathematical functions, and confidence factors for facts. The system also has a provision for fuzzy variables. With fuzzy variables the user was able to specify multiple answers to a question.[6] In graphics mode, the developer could create screens that allowed the user to input data from images means of a mouse.[6] Current expert systems provide the user with source code to build new features
Applications
VP-Expert has been utilized in various ways to fulfill needs in the medical field, law, business and applied science. It has been used to diagnose problems, to model and optimize systems, to provide training, and to automate repetitive tasks.
Medical uses are diagnosing gastrointestinal diseases,[7] a method to localize the hippocampus in human brain from MRI scans automatically [8]and training nurses.[9]A Sentencing Advisor is used by the legal community.[10]Two scientific uses are a system to balance airport capacity and noise mitigation, [11]and nuclear reactor safety analysis.[12] A business application supports analysts in the area of Mergers and Acquisitions.[13]
Critique
Expert systems were among the first forms of artificial intelligence (AI) software. The systems attempted to capture the expertise of specialists to make the knowledge available to others. Initially, this methodology was not available to the general public because of mainframe computer costs and complex programming requirements. A variety of expert system building tools for personal computers were developed in the 1980's that made this methodology available outside of universities and large corporations. VP-Expert was one of these systems.
Origins
VP-Expert was first published by Paperback Software International in 1984 and upgraded in 1985 and 1987.[1] In June 1991, ownership of VP-Expert was transferred to WordTech Systems, Inc. in 1991 after Paperback Software was liquidated. In 1992 Wordtech supported an upgrade to version 3.0. VP-Expert was widely used in the 1980’s, but usage declined in the early 1990’s.
The expert system shell was written in the C programming language. It was created and upgraded by Brian Sawyer,[1] author of Programming Expert Systems in Pascal[2]
Features
VP-Expert[3][4] [14] was rule-based expert system in which the knowledge engineer enters if-then rules. A knowledge base was developed, a collection of rules pertaining to the expertise of an area of knowledge. Induction was more direct means of entering the expertise, using a set of examples and observations by the user.[6] Currently, data mining is used to discover new knowledge in data unknown to the expert. Once the expert system was built, the expertise could be ported to end users using the IBM-PC. Current expert systems can be developed and ported to a range of machines from personal computers to supercomputers.<clips ref> VP-Expert could receive input from spreadsheets and database software. Rules could be backward chaining or forward chaining. VP-Expert includes hypertext, support for mathematical functions, and confidence factors for facts. The system also had a provision for fuzzy variables. With fuzzy variables the user was able to specify multiple answers to a question.[6] In graphics mode, the developer could create screens that allowed the user to input data from images means of a mouse.[6] Several current expert systems provide the user with source code to build new features into the system.
Applications
VP-Expert has been utilized in various ways to fulfill needs in the medical field, law, business and applied science. It has been used to diagnose problems, to model and optimize systems, to provide training, and to automate repetitive tasks.
Medical uses are diagnosing gastrointestinal diseases,[7] a method to localize the hippocampus in human brain from MRI scans automatically [8]and training nurses.[9]A Sentencing Advisor is used by the legal community.[10]Two scientific uses are a system to balance airport capacity and noise mitigation, [11]and nuclear reactor safety analysis.[12] A business application supports analysts in the area of Mergers and Acquisitions.[13]
Critique
Aspects of other widely used expert system pc shells, Level 5 Object, and Exsys Professional, may be compared to VP-Expert. LEVEL-5 Object has the most flexible inference methods, utilizing forward chaining, backward chaining, blackboard, and multiple hypotheses. EXSYS has a similar level of flexibility. VP-Expert primarily uses backward chaining and forward chaining rules.[15]VP-Expert has good demonstration capabilities, displaying the contents of the knowledge base knowledge base that it is currently searching, the active inference process, and the current state of working memory. EXSYS shows only the rules that are currently being applied. LEVEL-5 Object has minimal demonstration capabilities. [15]These systems must communicate well with the end-users to answer their questions and to give advice. Both LEVEL-5 Object and VP-Expert have good explanation capabilities while EXSYS is limited in this area.[15]All three packages can be integrated with Dbase, Lotus 1-2-3, and ACSII files. LEVEL-5 Object can also be integrated with FOCUS.[15]All the above systems use confidence calculations for the rules.
- ^ a b c d Rosu, Sebastian; Drago, George (2009). "A Knowledge Management Scenario to Support Knowledge Applications Development". Advances in Electrical and Computer Engineering. 9 (1): 8–15. Retrieved 2023-11-04.
- ^ a b Sawyer, Brian; Foster, Dennis. Programming Expert Systems in PASCAL. Wiley Press. ISBN 0471842672.
- ^ a b Costa, Ileana (1990). "Rapid Expert System Prototyping with Shells for Personal Computers". 1990 IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings: 902–908.
- ^ a b Brent, Edward (1988). "Expert System Shells for IBM-Compatible Microcomputers: A Comparative Review". Social Science Computer Review. 6 (1): 73–74.
- ^ Harmon, Paul (1988). Expert systems: tools and applications. John Wiley.
- ^ a b c d e f Ramsey, Martin (1989). "Gaining Proficiency in Expert Systems". Mechanical Engineering. 111 (4): 73–74. Retrieved 2023-11-05.
- ^ a b "Presenting an expert system for early diagnosis of gastrointestinal diseases". Retrieved 2023-10-19.
- ^ a b Soltanian-Zadeh, Hamid; Siadat, Mohammad-Reza (1999). "Knowledge-based localization of hippocampus in human brain,". Proceedings of the SPIE. 3661 (1): 1646–1655. Retrieved 2023-11-05.
- ^ a b Saleem, N (1994). "Expert systems as computer assisted instruction systems for nursing education and training". Comput. Nurs. 12 (1): 35–45.
- ^ a b Gruner, Richard (1989). "Federal Sentencing Advisor: An Expert Computer System for Federal Sentencing Analysis". Santa Clara high technology law journal. 5 (1): 51–73. Retrieved 2023-11-02.
- ^ a b Wayson (1989). "Use of a Knowledge-Based Expert System to Maximize Airport Capacity in Harmony with Noise-Mitigation" (PDF). Transportation Research Board: 31–41. Retrieved 2023-11-05.
- ^ a b Kobare, S.K. (1992). "Expert systems for emergency alarms analysis during accident situations in nuclear reactors". Reliability Engineering & System Safety. 37 (2): 139–149. Retrieved 2023-11-02.
- ^ a b Lyons, Patrick; Persek, Stephen (1991). "Integrating Neural Networks and Expert Systems for Merger and Acquisition Analysis". Proceedings of the First International Conference on Artificial Intelligence Applications on Wall Street, IEEE Computer Society: 200–205. Retrieved 2023-11-05.
- ^ Harmon, Paul (1988). Expert systems: tools and applications. John Wiley.
- ^ a b c d | Kim, Chung S.; Yoon, Youngohc (2016-02-01). "Evaluation of Four PC-Based Expert System Shells". Journal of Computer Information Systems. 32 (2): 46–49. Retrieved 2023-11-01.