Question

3. Historically, what were the differences between decision support and expert systems? What factors led to the narrowing of those differences? What implication does this have for the model management feature in DSS? 4. How do you know when you have included enough "intelligence" in a decision support system? 5. Compare and contrast symbolic processing and numerical processing. Why is the former referred to as "intelligence"? 6. What factors would lead you to recommend selecting a project that is appropriate for expert systems development? 7. Consider preparing a DSS for which certainty factors are relevant. This may be a class project, an example with which you are familiar, or a hypothetical example. What issues need to be tracked with certainty factors?

Answer 1

Question 3:

Answer: A decision support system can be described as a computer program that is specifically employed to support courses, judgments, and determinants within a business or in an organization. Whereas, expert systems are the parts of a computer that actively plays a significant role in decision making similar to human ability of reasoning.

The factors of automated systems or artificial intelligence systems in a certain field have narrowed down their differences. Often in certain fields, automated decision making is necessary and both the decision-making system and expert systems are combining in automated systems that make autonomous decisions.

The model management feature in decision-making system will gain more popularity with the merge of the expert systems and decision making systems because model management helps to simplify the reasoning and decision-making ability of an automated system.

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