The phrase "a representation language" is correct and usable in written English.
It can be used in contexts related to computer science, linguistics, or any field that involves formal systems for representing information.
Example: "In programming, a representation language is essential for defining the structure and semantics of data."
Alternatives: "a modeling language" or "a descriptive language".
We present ARTIGENCE, a representation language that combines description logics and Horn rules with uncertainty.
TnT comprises a representation language for structure and function that enables the construction, extension, and maintenance of the domain-specific knowledge base required for such inferences, and an evidential reasoning algorithm.
Tags may be represented by a representation language that enables for querying.
It requires a representation language and the capability of a knowledge processor to construe the meaning of concepts of that language.
The term heuristic power is used to describe the extent to which a knowledge representation language allows a knowledge-based system to draw inferences and solve problems within its intended domains of application.
Furthermore, a role definition language is given, and a policy representation language is discussed.
This provides a useful representation language in its own right, providing a compromise between heuristic and epistemic adequacy.
If we aim at a structure preserving design then notational convenience, i.e. the ease with which a knowledge representation language can be read, written, and understood, acquires a greater importance than the word "convenience" might suggest.
Inductive Logic Programming (ILP) is a subfield of machine learning, which originally relied on logic programming as a uniform representation language for expressing examples, background knowledge and hypotheses.
The algorithm is built upon an abstract representation language that provides a general and formal basis and serves as the vocabulary to define the planning problem.
In this case polynomial PAC-learnability holds if a different representation language is used.
