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Knowledge representation goes hand in hand with automated reasoning because one of the main purposes of explicitly representing knowledge is to be able to reason about that knowledge, to make inferences, assert new knowledge, etc. Virtually all knowledge representation languages have a reasoning or inference engine as part of the system.
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 ...
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 intelligence. Issues such as how to provide rational default assumptions and what humans consider common sense in a virtual environment.
Description logics (DL) are a family of formal knowledge representation languages. Many DLs are more expressive than propositional logic but less expressive than first-order logic . In contrast to the latter, the core reasoning problems for DLs are (usually) decidable , and efficient decision procedures have been designed and implemented for ...
In knowledge representation, a class is a collection of individuals or individuals objects. [1] A class can be defined either by extension (specifying members), or by intension (specifying conditions), using what is called in some ontology languages like OWL .
Schank developed the model to represent knowledge for natural language input into computers. Partly influenced by the work of Sydney Lamb, his goal was to make the meaning independent of the words used in the input, i.e. two sentences identical in meaning would have a single representation. The system was also intended to draw logical inferences.
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 ...
In artificial intelligence, symbolic artificial intelligence (also known as classical artificial intelligence or logic-based artificial intelligence) [1] [2] is the term for the collection of all methods in artificial intelligence research that are based on high-level symbolic (human-readable) representations of problems, logic and search. [3]