KL-ONE
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A KL-ONE is a frame-based system that is used as a deductive classifier in automated reasoning of structured inheritance networks.
- Context:
- It was initially develped by developed by Brachman & Schmolze, 1985.
- …
- Counter-Example(s)
- See: Knowledge-based System, Ontology Language, Frame Language, Multiple Inheritance.
References
2017
- (Wikipedia, 2016) ⇒ http://en.wikipedia.org/wiki/KL-ONE
- KL-ONE (pronounced "kay ell won") is a well known knowledge representation system in the tradition of semantic networks and frames; that is, it is a frame language. The system is an attempt to overcome semantic indistinctness in semantic network representations and to explicitly represent conceptual information as a structured inheritance network.[1][2][3]
- There is a whole family of KL-ONE-like systems. One of the innovations that KL-ONE initiated was the use of a deductive classifier, an automated reasoning engine that can validate a frame ontology and deduce new information about the ontology based on the initial information provided by a domain expert.
- Frames in KL-ONE are called concepts. These form hierarchies using subsume-relations; in the KL-ONE terminology a super class is said to subsume its subclasses.
- Multiple inheritance is allowed. Actually a concept is said to be well-formed only if it inherits from more than one other concept. All concepts, except the top concept (usually THING), must have at least one super class.
- In KL-ONE descriptions are separated into two basic classes of concepts: primitive and defined. Primitives are domain concepts that are not fully defined. This means that given all the properties of a concept, this is not sufficient to classify it. They may also be viewed as incomplete definitions. Using the same view, defined concepts are complete definitions. Given the properties of a concept, these are necessary and sufficient conditions to classify the concept.
- The slot-concept is called roles and the values of the roles are role-fillers. There are several different types of roles to be used in different situations. The most common and important role type is the generic RoleSet that captures the fact that the role may be filled with more than one filler.
1999
- (Nebel, 1999) ⇒ Bernhard Nebel, (1999). https://www.csee.umbc.edu/courses/771/papers/nebel.html
- These two points are addressed by the so-called description logics (also called terminological logics, concept languages, and attributive description languages; Nebel and Smolka 1991), which formalize the declarative part of frame-based systems and grew out of the development of the frame-based system KL-ONE (Brachman and Schmolze 1985). In description logics, it is possible to build up a concept hierarchy out of atomic concepts (interpreted as unary predicates and denoted by capitalized words) and attributes, usually called roles (interpreted as binary predicates and denoted by lowercase words). The intended meaning of atomic concepts can be specified by providing concept descriptions made up of other concepts and role restrictions, as in the following informal example:
- Woman = Person and Female
- Parent = Person with some child
- Grandmother = Woman with some child who is a Parent
- These two points are addressed by the so-called description logics (also called terminological logics, concept languages, and attributive description languages; Nebel and Smolka 1991), which formalize the declarative part of frame-based systems and grew out of the development of the frame-based system KL-ONE (Brachman and Schmolze 1985). In description logics, it is possible to build up a concept hierarchy out of atomic concepts (interpreted as unary predicates and denoted by capitalized words) and attributes, usually called roles (interpreted as binary predicates and denoted by lowercase words). The intended meaning of atomic concepts can be specified by providing concept descriptions made up of other concepts and role restrictions, as in the following informal example:
1985
- (Brachman & Schmolze, 1985) ⇒ Brachman, Ronald J., and James G. Schmolze. "An overview of the KL-ONE knowledge representation system." Cognitive science 9.2 (1985): 171-216. doi: 10.1016/S0364-0213(85)80014-8
- ABSTRACT: KL-ONE is a system for representing knowledge in Artificial Intelligence programs. It has been developed and refined over a long period and has been used in both basic research and implemented knowledge-based systems in a number of places in the AI community. Here we present the kernel ideas of KL-ONE, emphasizing its ability to form complex structured descriptions. In addition to detailing all of KL-ONE's description-forming structures, we discuss a bit of the philosophy underlying the system, highlight notions of taxonomy and classification that are central to it, and include an extended example of the use of KL-ONE and its classifier in a recognition task.
- ↑ Woods, W. A.; Schmolze, J. G. (1992). "The KL-ONE family". Computers & Mathematics with Applications 23 (2–5): 133. doi:10.1016/0898-1221(92)90139-9.
- ↑ Brachman, R. J.; Schmolze, J. G. (1985). "An Overview of the KL-ONE Knowledge Representation System". Cognitive Science 9 (2): 171. doi:10.1207/s15516709cog0902_1.
- ↑ D.A. Duce, G.A. Ringland (1988). Approaches to Knowledge Representation, An Introduction. Research Studies Press, Ltd.. ISBN 0-86380-064-5.