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7. CONCLUSIONSArtificial Intelligence (AI) technology is filling an essential need in telecommunications management tasks as networks grow in size, complexity, and importance. When conventional software approaches become severely stressed in certain areas, expert systems using AI technology have been demonstrated as viable alternative solutions. This chapter first lays out the overall picture of telecommunications management tasks, and then identifies those tasks where expert systems have made significant contributions. To benefit future expert system developers, it characterizes telecommunications domains and provides a list of commonly used AI techniques, where each of the techniques is described in terms of its main strength and weakness, plus its possible application tasks. In addition, this chapter describes some recent fielded expert systems in both wireline and wireless communication domains and sheds some light on the current state-of-the-art. Finally, it discusses development methodology, lists common development pitfalls found in telecommunications domains, and addresses research issues by challenging AI techniques for some currently needed tasks. In the future, intelligent networks will self-diagnose, engage in distributed cooperative problem-solving, and perform proactive network management. People will have instant access to the information highway through intelligent agents that can navigate heterogeneous data sources, finding and presenting the information they need. Office and home computers will behave as smart telephones loaded with capabilities such as speech recognition, natural language translators and schedulers, and handle voice, fax, data, and video seamlessly. Clearly, AI will play an important enabling role in the communications network of the future. REFERENCES
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