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Chapter 24
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1. | Introduction | |
2. | Background | |
3. | Telecommunications Domains and Potential Tasks | |
4. | AI Techniques | |
4.1. | Rule-Based Systems | |
4.2. | Search | |
4.3. | Neural Networks | |
4.4. | Decision Trees and Case-Based Reasoning | |
4.5. | Model-Based Reasoning | |
4.6. | Distributed Artificial Intelligence | |
4.7. | Approximate Reasoning | |
4.8. | Hybrid Systems | |
5. | Applications | |
5.1. | Wireline Communication | |
5.2. | Wireless or Satellite Communication | |
6. | Lessons and Research Issues | |
7. | Conclusions | |
References |
Telecommunications is one of the most rapidly growing industries worldwide. In developing countries, there is a huge market to offer both wireline and wireless telephone services. The majority of people there simply do not have the basic telephone service. Many of these countries have started to privatize their telephone industry. In the developed countries such as the U.S., the explosion of Internet usage and the growth of personal computers are forcing telecommunications companies to expand the facility to offer both data and voice services. As the deregulation of the telephone industry gradually opens up the U.S. market for competition, telecommunications companies here will rely on advanced technologies for competitive leverage.
One such technology is the expert system technology that enables telecommunications companies to offer improved products and services at low cost. Expert systems in this context are computer programs that emulate the behavior of telecommunications experts and automate the operation of telecommunications systems using artificial intelligence techniques. Telecommunications expertise is a critical corporate asset, especially when companies are losing experts due to fierce competition and early retirement. New telecommunications technologies in the area of wireless and digital data services require skilled technicians to operate. Expert systems can help capture the knowledge and heuristics acquired by the experts over many years of experience and train a young generation of technicians to use and maintain advanced telecommunications systems.
Since the first bloom of expert systems in the early 1980s, the telecommunications industry has been in the forefront of applying expert system technology (Liebowitz, 1988; Liebowitz, 1995). Various expert systems have been developed for network diagnosis, repair, and maintenance. Yet, there is still room for expert system applications to meet the demand. The goal of this chapter is to bridge the gap between expert systems and telecommunications domains, and to make artificial intelligence techniques commonly accessible tools to accomplish some of important telecommunications tasks.
This chapter starts with some background information on telecommunications management and the application history of expert systems in this field. It then characterizes telecommunications domains and corresponding tasks, and describes common artificial intelligence techniques. This is followed by presenting some fielded applications that use these techniques. Finally, it draws some lessons and outlines future research and development directions.
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