GUPTA For his supervision of the thesis and his willingness to support my last minute revisions
نویسندگان
چکیده
A recent innovation in artificial intelligence research has been the integration of multiple artificial intelligence techniques into hybrid intelligent systems. Hybrid artificial intelligent systems seek to overcome the deficiencies of traditional artificial techniques by combining techniques with complementary capabilities. Using these hybrid systems, researchers have been able to solve a variety of complex classes of problems otherwise intractable by use of individual systems. This research examines the state of the art in hybrid intelligent systems that combine such popular techniques as expert systems, case-based reasoning systems, fuzzy logic, neural networks, genetic algorithms. Comparisons and conclusions concerning the general capabilities of such systems are given. Additionally a case study is conducted of a complex multisource information system. The applicability of hybrid artificial intelligence techniques to optimize the system is ascertained and a hybrid artificial intelligent system design proposed and justified. Thesis Supervisor: Amar Gupta Title: Co-Director, Productivity from Information Technology (PROFIT) Initiative. MIT School of Management
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