1. ES: Expert Systems n Knowledge Base (facts, rules) n Inference Engine (software) n User Interface

2. EXPERT SYSTEMS n Expert system: Information system that applies reasoning capabilities and stored knowledge to reach a conclusion (low level “AI”). n Collect, store, formalize and use large stores of task specific expertise n What is expertise? –Knowledge: Structured information –Heuristics: Rules of thumb compiled from experience n Simple example: “Diagnosing” whales http://www.aiinc.ca/demos/whale.html

3. The Expert System Knowledge Base User Workstation Drivers with Pagers Expert Advice User Interface Programs User Interface Programs Inference Engine Program Inference Engine Program Expert System Development Workstation Knowledge Engineering Knowledge Acquisition Program Knowledge Acquisition Program Expert and/or Knowledge Engineer EXPERT SYSTEM COMPONENTS

4. Expert Systems Example n ITT Commercial Finance Corp., Expert Credit System (ECS) n Uses experience and knowledge of senior credit managers. n Analyzes credit information, identifies credit proposal strengths and weaknesses, makes recommendations. n Available to all decision-making managers (user- friendly, as well). n 23 offices, 250 users. n $500,000 savings in hard costs, $1 M bad loan write off savings estimated.

5. EXAMPLE: CREDIT CARDS n American Express does not have fixed account limits, but instead decides each credit authorization on a case-by-case basis. What might be some rules or heuristics for this decision process?

6. Expert Systems Examples n Karl Irwin gets engaged. n Diagnosing illnesses.

7. EXAMPLE: CHOOSING WINES n What are relevant facts about wines and meals? n What are some example rules of thumb for pairing different kinds of wine with different kinds of meals?

8. WINE EXAMPLE: FACTS

9. WINE EXAMPLE: IF-THEN RULES

11. n Domain: Narrow and well defined n Expertise: Requires true expertise in short supply n Complexity: Problem is too complex for conventional programming n Structure: Solution process must cope with ill-structure, uncertainty, missing data n Availability: Have a willing, articulate expert!! WHEN IS AN EXPERT SYSTEM APPROPRIATE?

12. DSS vs. Expert System DSS: –Fixed models and formulas –Usually user driven; user has expertise, user asks the questions –Does not explain answers Expert system –Mimics human reasoning abilities –Usually machine driven; machine has expertise; machine asks the questions –Has explanation facility