微小型专家系统实验报告.doc

Contents & Requirements

Acquaint and acquire the principles of rule-based expert system.
Use CLIPS which is a programmable tool of expert system to write a program. Choose a breakdown diagnosis-based knowledge area, for example, TV, auto and etc. Use production formula rule to formalize the book learning. Put into the CLIPS system. Set up knowledge base.
Set up necessary I/O interface. Compose a simple diagnosis expert system.

Choose a breakdown diagnosis-based knowledge area as the application area of expert system.
Use the decision tree to further define the area of diagnosis. Formalize the related knowledge.
Use CLIPS to set up knowledge base.
Design user interface and I/O information.
Design the detail methods and write a program. Realize the designed expert system.
principles of rule-based expert systems
In the evolution course puting, a field called artificial intelligence was developed in the 70s and 80s with an aim to puters reason like human beings. Rule-based programming paradigm emerged at that time as ways to implement systems that appear to think and reason like human beings. Examples of rule-based systems are expert systems that have the knowledge of a doctor or a tax advisor and can plex questions people would normally ask those professionals.
The idea of rule-based programming is to represent a domain expert’s knowledge in a form called rules. That’s why it’s called rule-based. Besides rules, another important ingredient in a rule-based system is facts. Here’s an example. Say John is a weather reporter who gives advice to people on TV channels based on weather conditions. Here’s John’s knowledge about weather:
If it’s a rainy day, advise people to bring umbrellas when they go out.
If it’s a rainy day, the road would be slippery because of the rain and hence warn people to drive more carefully.
How do we represent the knowledge in a rule-based system? We represent it as rules and facts like this: