An analysis of the development and limitations of expert systems and neural networks.
Written in 2004; 4,924 words; 32 sources; MLA; $ 125.95
Paper Summary:
This paper provides an examination of the concepts and technologies needed to develop, implement and integrate expert systems and neural networks. The limitations of expert systems and their alternatives are discussed, followed by an analysis of the relevant and scholarly literature covering neural networks. A summary of the research is provided in the conclusion.
Outline
Introduction
Review and Discussion
Background and Overview
Expert Systems
Neural Networks
Constraints to Effective Use of AI Applications
Conclusion
From the Paper:
"Artificial Intelligence (AI) as a formal discipline is certainly not new, having been around for more than 50 years (Gozzi 1997). Nevertheless, AI remains a term that frequently "conjures images of HAL's refusal to open the pod bay doors or Deep Blue winning the world chess championship. But artificial intelligence (or Al) is not a phenomenon restricted to science fiction movies and chess tournaments; it has rapidly, if silently, become a fixture of daily life" (Gibson 2003:83). In fact, Kapoor (2003) emphasizes that there can be no dispute that machines with greater-than-human intelligence will be built in the next 50 years, and the creation of such AI empowered creations will have far-reaching implications for all aspects of society, science, technology, and the environment."
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