Ontologies

Swartout, William; Tate, Austin

doi:10.1109/mis.1999.747901

Cited by 117 publications

(34 citation statements)

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“…Ontology [6], concept maps [7], frames, rules and constraints [8] are intended to present distinct pieces of knowledge that are worth representing differently. Note that an important distinction is between ontological, factual and rule-based knowledge.…”

Section: Encoded Vs Represented Knowledgementioning

confidence: 99%

Knowledge Representation for Cognitive Robotic Systems

Vassev

Hinchey

2012

2012 IEEE 15th International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops

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Section: Encoded Vs Represented Knowledgementioning

confidence: 99%

Knowledge Representation for Cognitive Robotic Systems

Vassev

Hinchey

2012

2012 IEEE 15th International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops

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“…Each knowledge corpus is structured into a special domain-specific ontology [14] and a logical framework. The domain-specific ontology gives a formal and declarative representation of the knowledge domain in terms of explicitly described domain concepts, individuals (or objects) and the relationships between those concepts/individuals.…”

Section: Ascens and Ascens Knowledge Basementioning

confidence: 99%

Representing Knowledge in Robotic Systems with KnowLang

Vassev

Hinchey

2012

Communications in Computer and Information Science

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Abstract. Building intelligent robotic systems is both stirring and extremely challenging. Researchers have realized that robot intelligence can be achieved with a logical approach, but still AI struggles to connect that abstract logic with real-world meanings. This paper presents KnowLang, a new formal language for knowledge representation in a special class of intelligent robotic systems termed ASCENS. Autonomic Service-Component Ensembles (ASCENS) are multi-agent systems formed as mobile, intelligent and open-ended swarms of special autonomic service components capable of local and distributed reasoning. Such components encapsulate rules, constraints and mechanisms for self-adaptation and acquire and process knowledge about themselves, other service components and their environment. In this paper, a brief KnowLang case study of knowledge representation for a robotic system is presented.

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“…Ontologies can be differentiated in two aspects, conceptual and formal logical nature. According to (Swartout & Tate, 1999), the first aspect has the task of depicting and composing structures of reality. The second addresses the creation of the semantic framework with the definition of objects, classes and contexts.…”

Section: State Of the Art -Modelling Approaches For System Representamentioning

confidence: 99%