Inference engine
component of the system that applies logical rules to the knowledge base to deduce new information
In the field of artificial intelligence, an inference engine is a software component of an intelligent system that applies logical rules to the knowledge base to deduce new information. The first inference engines were components of expert systems. The typical expert system consisted of a knowledge base and an inference engine. The knowledge base stored facts about the world. The inference engine applied logical rules to the knowledge base and deduced new knowledge. This process would iterate as each new fact in the knowledge base could trigger additional rules in the inference engine. Inference engines work primarily in one of two modes either special rule or facts: forward chaining and backward chaining. Forward chaining starts with the known facts and asserts new facts. Backward chaining starts with goals, and works backward to determine what facts must be asserted so that the goals can be achieved.
Additionally, the concept of 'inference' has expanded to include the process through which trained neural networks generate predictions or decisions.
The public source identifies “Inference engine” as component of the system that applies logical rules to the knowledge base to deduce new information. This brief keeps that definition visible, then builds a research path around Inference, engine and component.
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This entry incorporates text from “Inference engine” on English Wikipedia. Contributors are listed in the page history. Text is available under the Creative Commons Attribution-ShareAlike 4.0 License. Selected authority identifiers and statements are retrieved from Wikidata under CC0; their references and qualifiers remain part of the verification path.