Overview
Popular in the 1970s and 80s, expert systems were the first truly successful AI applications. They rely on a 'knowledge base' of facts and a 'reasoning engine' to solve complex problems.
Components
- Knowledge Base: A collection of domain-specific rules and facts provided by human experts.
- Inference Engine: Applies logical rules to the knowledge base to deduce new information or provide recommendations.
- User Interface: Allows users to interact with the system and receive explanations for its decisions.
Legacy
While largely replaced by modern machine learning, the principles of expert systems live on in business rule engines and certain types of diagnostic software.