What does the term 'expert systems' refer to in AI?

The term "expert systems" in artificial intelligence specifically refers to computer programs that emulate the decision-making ability of a human expert in a particular domain. These systems are designed to solve complex problems by reasoning through bodies of knowledge, represented primarily as if-then rules. This knowledge-based approach allows expert systems to analyze data and provide solutions or recommendations based on their programmed knowledge.

Unlike general AI, which aims for human-like intelligence across diverse tasks, expert systems focus on narrow domains, such as medical diagnosis, financial forecasting, or troubleshooting technical problems. They rely on a well-defined set of rules and knowledge bases that are typically curated by human experts.

The other options describe different aspects of AI that do not specifically align with the focused and rule-based nature of expert systems. For instance, general human-like intelligence denotes broader capabilities, while technologies operating without guidance imply a lack of structured expertise. Lastly, virtual assistants, while intelligent in their use of natural language processing and user interaction, differ substantially from expert systems that provide specialized domain knowledge through explicit reasoning.