TY - CHAP
T1 - KnowLang – A Formal Specification Model for Self-adaptive Systems
AU - Hinchey, Mike
AU - Vassev, Emil
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - KnowLang is a framework for knowledge representation and reasoning (KR &R) that aims at efficient and comprehensive knowledge structuring and awareness based on logical and statistical reasoning. It tackles both explicit representation of domain concepts and relationships and explicit representation of particular and general factual knowledge, in terms of predicates, names, connectives, quantifiers and identity. Moreover, it handles uncertain knowledge in which additive probabilities are used to represent degrees of belief. Other remarkable features are related to knowledge cleaning and knowledge representation for autonomic self-adaptive behaviour. Knowledge specified with KnowLang takes the form of a Knowledge Base (KB) that outlines a KR context. A special KnowLang Reasoner operates in this context to allow for knowledge querying and update. In addition, the reasoner can infer special self-adaptive behaviour. At its very core, KnowLang is a formal specification language providing a comprehensive specification model aiming at addressing the knowledge representation problem of self-adaptive systems. The complexity of the problem necessitated the use of a specification model where knowledge can be presented at different levels of abstraction and grouped by following both hierarchical and functional patterns. In this paper, we outline the formal semantics of the KnowLang multi-tier specification model. The model is outlined in terms of layers dedicated to knowledge corpuses, KB operators, and inference primitives.
AB - KnowLang is a framework for knowledge representation and reasoning (KR &R) that aims at efficient and comprehensive knowledge structuring and awareness based on logical and statistical reasoning. It tackles both explicit representation of domain concepts and relationships and explicit representation of particular and general factual knowledge, in terms of predicates, names, connectives, quantifiers and identity. Moreover, it handles uncertain knowledge in which additive probabilities are used to represent degrees of belief. Other remarkable features are related to knowledge cleaning and knowledge representation for autonomic self-adaptive behaviour. Knowledge specified with KnowLang takes the form of a Knowledge Base (KB) that outlines a KR context. A special KnowLang Reasoner operates in this context to allow for knowledge querying and update. In addition, the reasoner can infer special self-adaptive behaviour. At its very core, KnowLang is a formal specification language providing a comprehensive specification model aiming at addressing the knowledge representation problem of self-adaptive systems. The complexity of the problem necessitated the use of a specification model where knowledge can be presented at different levels of abstraction and grouped by following both hierarchical and functional patterns. In this paper, we outline the formal semantics of the KnowLang multi-tier specification model. The model is outlined in terms of layers dedicated to knowledge corpuses, KB operators, and inference primitives.
KW - formal specification
KW - KnowLang
KW - self-adaptive systems
UR - http://www.scopus.com/inward/record.url?scp=85171997290&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-40436-8_14
DO - 10.1007/978-3-031-40436-8_14
M3 - Chapter
AN - SCOPUS:85171997290
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 367
EP - 392
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PB - Springer Science and Business Media Deutschland GmbH
ER -