Expert SystemsCategories of Expert System
There are 4 categories of expert system:
Classification
Diagnosis
Advise
Planning
Components of an Expert System
An expert system has 3 components:
The Knowledge Base - Where the information is stored in the expert system in the form of facts and rules (basically a series of IF statements). This is where the programmer writes the code for the expert system.
The User Interface - Where the user interacts with the expert system. In other words where questions are asked, and advice is produced. As well as the advice that is output, the user interface can output the justification featutes of an expert system. This is either How justification - where the system justifies its reasoning for providing a piece of advice or Why justification - where the system
justifies why a particular question is being asked.
Justification allows the user piece of mind about why a question is asked or a piece of advice is provided, and can increase their confidence in taking such advice.
It also
makes it easier for the programmer of the system to ensure that it works correctly as it will flag up areas where the expert system provides advice that is not intended by the programmer.
Inference Engine - This applies the facts to the rules and determines the questions to be asked of the user in the user interface and in which order to ask them. This is the 'invisible' part of the expert system, which is active during a consultaion of the system (when the user choses to run the program).
An expert system can use 2 different methods of inferencing - Forward Chaining and Backward Chaining.
A Backward Chaining system (a goal driven system)works with the system assuming a hypothesis oo what the likely outcome will be, and the system then works backwards to collect the evidence that would support this conclusion. Expert sysetms used for planning often use backward chaining.
A Forward Chaining expert system (a data driven system) simply gathers facts (like a detective at the scene of a crime) until enough evidence is collected that points to an outcome. Forward chaining is often used in expert systems for diagnis, advise and classification, although the size and complexity of the system can play a part in deciding which method of inferencing to use.
Forward chaining is examined in more details in Conflict Resolution
