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CSE 335/435: Intelligent Decision Support Systems Fall Semester 2006 An Example of a commercial system (click on Yoda for a link to an intelligent decision.

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Presentation on theme: "CSE 335/435: Intelligent Decision Support Systems Fall Semester 2006 An Example of a commercial system (click on Yoda for a link to an intelligent decision."— Presentation transcript:

1 CSE 335/435: Intelligent Decision Support Systems Fall Semester 2006 An Example of a commercial system (click on Yoda for a link to an intelligent decision support system)

2 How this works? Game? Tie Fighter Version? Win95 … Mouse settings… This is an example of a Conversational Case-Based Reasoning Process Case: (animated slide. Click once at a time)

3 Other Fielded Applications IBM NCR Gateway Daimler-Benz Intel 3Com LucasArts Broderbund Hewlett Packard PeopleSoft American Airlines Chrysler AT&T BT Freightliner Groupe Bull MCI Microsoft Los Angeles Times National Westminster Bank Ordnance Survey Orange Personal Communications Scottish Hydro Siemens AG South Western Electricity Southern Electric Compaq VISA International Xerox Yorkshire Water Services Nokia Telecommunications United Utilities Halifax Building Society List of some of Inference/eGain’s costumers using a IDSS tool

4 CSE 335/435: Intelligent Decision Support Systems Fall Semester 2006 Studies algorithms for building decision support systems Focus on Knowledge-based systems Prerequisites: –AI, or –Algorithms, or –Senior status, or –CSE/CompE Graduate student Two variants: –CSE 335: applications –CSE 435: applications + computational complexity theory (therefore, counts as a theory course for the MS/PhD program)

5 Computational Complexity Programming project Applications to IDSS:  Analysis Tasks  Help-desk systems  Classification  Diagnosis  Tutoring  Synthesis Tasks  Software Engineering  E-commerce  Knowledge Management AI  Introduction  Overview Machine Learning  Attribute-Value Rep.  Decision Trees  Induction CBR  Introduction  Representation  Similarity  Retrieval  Adaptation Rule-based Inference  Rule-based Systems  Expert Systems Topics Covered and Relations Synthesis Tasks  Planning  Configuration Uncertainty (MDP, Utility, Fuzzy logic) (animated slide. Click once at a time)


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