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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.
Knowledge retrieval seeks to return information in a structured form, consistent with human cognitive processes as opposed to simple lists of data items. It draws on a range of fields including epistemology (theory of knowledge), cognitive psychology, cognitive neuroscience, logic and inference, machine learning and knowledge discovery, linguistics, and information technology.
Text inferencing describes the tacit or active process of logical induction or deduction during reading. Inferences are used to bridge current text ideas with antecedent text ideas or ideas in the reader's store of prior world knowledge. Text inferencing is an area of study within the fields of cognitive psychology and linguistics. Much of the ...
Because the list of goals determines which rules are selected and used, this method is called goal-driven, in contrast to data-driven forward-chaining inference. The backward chaining approach is often employed by expert systems. Programming languages such as Prolog, Knowledge Machine and ECLiPSe support backward chaining within their inference ...
Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.
DIP, Defeasible-Inference Platform (DIP) is an Web Ontology Language reasoner and Protégé desktop plugin for representing and reasoning with defeasible subsumption. [3] It implements a Preferential entailment style of reasoning that reduces to "classical entailment" i.e., without the need to modify the underlying decision procedure.
Participants in interpretive discussions are asked to interpret various aspects of texts or to hypothesize about intended interpretations using text-based evidence. Other types of discussion questions include fact-based and evaluative questions. Fact-based questions tend to have one valid answer and can involve recall of texts or specific passages.
A good indexing strategy is a major factor in deciding the overall performance of a production system, especially when executing rule sets that result in highly combinatorial pattern matching (i.e., intensive use of beta join nodes), or, for some engines, when executing rules sets that perform a significant number of WME retractions during ...