An expert system is a computer program that stores the know-how of human specialists as rules and facts and draws conclusions from them. It typically consists of a knowledge base and an inference engine that applies the rules. Expert systems shaped AI in the 1970s and 1980s, for example in medical diagnosis or configuring technical equipment. Their ideas live on today in rule-based checks and knowledge graphs.
Knowledge engineering covers capturing, organising and preparing expert knowledge so that IT systems can use it. Originally it focused on rules for expert systems; today the priority is often to document scattered knowledge from manuals, process descriptions and people's heads so that AI agents can answer reliably from it. This involves clear structures, up-to-date sources, defined responsibilities and closing identified gaps.
Heuristics are rules of thumb or simplified strategies that lead to a good, though not guaranteed optimal, solution within reasonable time. In computer science and AI they help narrow down huge search spaces – for example in route planning, where the straight-line distance to the destination serves as an estimate, or in chess, where positions are evaluated. People also use heuristics in everyday life and business decisions, with the risk of systematic thinking errors.
In computer science, an ontology is a formal model of a subject area that clearly defines concepts, their properties and the relationships between them. This allows people and machines to interpret data consistently and draw conclusions from it. Ontologies underpin many knowledge graphs, semantic search systems and data integration projects. Example: a product ontology states that an “e-bike” is a “bicycle” and has a “battery”.
A decision tree is a model that represents a decision as a sequence of simple yes/no questions: each branch tests one feature and each leaf gives an outcome. In machine learning, such trees are learnt automatically from data and used for classification or forecasting. Their main strength is transparency – for instance, showing why a loan application was flagged based on income, term and payment history.
