inferentsimootori

An inferentsimootori (inference engine) is a software component that derives new information from a knowledge base by applying a set of rules, logic, or probabilistic models. It is a central element of many AI systems and expert systems, enabling automated reasoning, decision support, and problem solving.

A typical inferentsimootori comprises a knowledge base (facts and rules), a working memory, and the inference mechanism. The engine evaluates rules against known facts to deduce new information, which is then stored for subsequent reasoning. Two common strategies are forward chaining, which starts from facts to reach conclusions, and backward chaining, which works from goals to required data.

Implementation often relies on pattern matching and rule evaluation. The Rete algorithm is a well-known technique to speed up rule-based inference. Logic-based engines may use Horn clause resolution or query-driven evaluation, while probabilistic or fuzzy extensions handle uncertainty in data and rules. Many systems support explanations, or justifications, for deduced conclusions.

Inferentsimootori concepts originated in early expert systems of the 1970s–1980s, with notable applications in medical diagnosis, troubleshooting, and configuration. In programming languages, Prolog provides a built-in inference mechanism based on logical rules. Today, inference engines are used in business rules management, AI assistants, and decision support systems, often in conjunction with machine learning components.

Limitations include knowledge acquisition bottlenecks, brittleness when knowledge is incomplete, and scalability challenges. Explainability and maintenance of the knowledge base are ongoing concerns. Hybrid approaches combine learned models with explicit rules to improve robustness and transparency.