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Knowledge management products adopted the term "knowledge-base" to describe their repositories but the meaning had a big difference. In the case of previous knowledge-based systems, the knowledge was primarily for the use of an automated system, to reason about and draw conclusions about the world.
[6] Expert systems gave us the terminology still in use today where AI systems are divided into a knowledge base, which includes facts and rules about a problem domain, and an inference engine, which applies the knowledge in the knowledge base to answer questions and solve problems in the domain. In these early systems the facts in the ...
The knowledge base contains domain-specific facts and rules [1] about a problem domain (rather than knowledge implicitly embedded in procedural code, as in a conventional computer program). In addition, the knowledge may be structured by means of a subsumption ontology, frames, conceptual graph, or logical assertions. [2]
A natural language processing process can be attached to the commonsense knowledge base to allow the knowledge base to attempt to answer questions about the world. [2] Common sense knowledge also helps to solve problems in the face of incomplete information. Using widely held beliefs about everyday objects, or common sense knowledge, AI systems ...
Pronounced "A-star". A graph traversal and pathfinding algorithm which is used in many fields of computer science due to its completeness, optimality, and optimal efficiency. abductive logic programming (ALP) A high-level knowledge-representation framework that can be used to solve problems declaratively based on abductive reasoning. It extends normal logic programming by allowing some ...
Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]
A key component of the system architecture for all expert systems is the knowledge base, which stores facts and rules for problem-solving. [53] The simplest approach for an expert system knowledge base is simply a collection or network of production rules. Production rules connect symbols in a relationship similar to an If-Then statement.
The knowledge base is divided into microtheories. Unlike the knowledge base as a whole, each microtheory must be free from monotonic contradictions. Each microtheory is a first-class object in the Cyc ontology; it has a name that is a regular constant. The concept names in Cyc are CycL terms or constants. [6]