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Knowledge representation and reasoning (KRR, KR&R, or KR²) is a field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can use to solve complex tasks, such as diagnosing a medical condition or having a natural-language dialog.
A frame language is a technology used for knowledge representation in artificial intelligence. They are similar to class hierarchies in object-oriented languages although their fundamental design goals are different. Frames are focused on explicit and intuitive representation of knowledge whereas objects focus on encapsulation and information ...
The most powerful form of knowledge representation is first-order logic. However, it is not possible to implement knowledge representation that provides the complete expressive power of first-order logic. Such a representation will include the capability to represent concepts such as the set of all integers which are impossible to iterate through.
Class (knowledge representation) Closed-world assumption; Cognitive categorization; Cognitive map; Colon classification; Completeness (knowledge bases) Composite Capability/Preference Profiles; Composite portrait; Computer Science Ontology; Concept map; Concepticon; Conceptual graph; Conceptualization (information science) Consistency ...
The Winograd schema challenge (WSC) is a test of machine intelligence proposed in 2012 by Hector Levesque, a computer scientist at the University of Toronto.Designed to be an improvement on the Turing test, it is a multiple-choice test that employs questions of a very specific structure: they are instances of what are called Winograd schemas, named after Terry Winograd, professor of computer ...
John McCarthy and Patrick J. Hayes defined this problem in their 1969 article, Some Philosophical Problems from the Standpoint of Artificial Intelligence. In this paper, and many that came after, the formal mathematical problem was a starting point for more general discussions of the difficulty of knowledge representation for artificial ...
In a model-based reasoning system knowledge can be represented using causal rules. For example, in a medical diagnosis system the knowledge base may contain the following rule: ∀ {\displaystyle \forall } patients : Stroke(patient) → {\displaystyle \rightarrow } Confused(patient) ∧ {\displaystyle \land } Unequal(Pupils(patient))
In knowledge representation and reasoning, a knowledge graph is a knowledge base that uses a graph-structured data model or topology to represent and operate on data. Knowledge graphs are often used to store interlinked descriptions of entities – objects, events, situations or abstract concepts – while also encoding the free-form semantics ...