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Learning Systems and Their Applications : Future of Strategic Expert System
| Content Provider | Semantic Scholar |
|---|---|
| Author | Duggal, Sudesh M. Chhabra, Rahul |
| Copyright Year | 2002 |
| Abstract | “Learning” denotes that a system is capable of adapting to a task, such that when the task is repeatedly performed the system will perform the task more efficiently than on previous attempts. Learning system may incorporate neural networks, fuzzy logic, genetic learning, self-learning expert systems, or a combination of any or all of these technologies. These systems are capable of the self-generation of mathematical, logical, or analytical rules for determining desired outputs based upon some input criteria or user assistance. Some of these systems are selftraining; others require training and/or previous knowledge in order to learn. Learning systems can be hardware or software-based, or a combination of both. Today, a great deal of research incorporating machine-learning techniques continues in the area of Artificial Intelligence. The purpose of this paper is to discusses their strategic applications, advantages and problems of learning systems, then focus on how these technologies are being used for developing solutions to difficult, yet strategic decisions, and finally present recommendations for how future systems will have to differ from current systems. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://iacis.org/iis/2002/DuggalChhabra.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
