reeglipõhine

Reeglipõhine is an Estonian term used to describe approaches and systems that base their operation on explicitly stated rules rather than solely on learned patterns or probabilistic models. In computer science and information processing, a reeglipõhine system relies on a set of IF-THEN rules to convert data into conclusions or actions, with the rules representing domain knowledge encoded by experts.

A typical reeglipõhine architecture includes a knowledge base containing production rules, a working memory with current facts, and an inference engine that matches rules to the available data. The engine may perform forward chaining, deriving new facts from existing ones, or backward chaining, working from a goal to determine which rules apply. Rule conflicts are resolved using predefined strategies such as rule priority, recency of facts, or specificity of conditions. The approach emphasizes transparency, as each decision can be traced to specific rules.

Benefits of reeglipõhine systems include interpretability and ease of updating when domain knowledge changes. They are well suited for domains with clear, well-defined procedures and where human experts can articulate the rules. They can also facilitate regulatory compliance and auditing, since the reasoning path is explicit.

Limitations include difficulties scaling to large rule sets, maintenance overhead, and brittleness in the face of unforeseen inputs. Handling uncertainty or learning from data typically requires hybrid approaches that combine rule-based components with statistical or machine learning techniques.

Common applications span medical decision support, fraud detection, regulatory compliance, customer support automation, and certain natural language processing tasks where rule-based grammars or heuristics are advantageous. The concept has historical roots in early expert systems and remains in use in hybrid AI architectures today.