Description Logic


Description Logics and Planning

AI Magazine

This article surveys previous work on combining planning techniques with expressive representations of knowledge in description logics to reason about tasks, plans, and goals. Description logics can reason about the logical definition of a class and automatically infer class-subclass subsumption relations as well as classify instances into classes based on their definitions. Descriptions of actions, plans, and goals can be exploited during plan generation, plan recognition, or plan evaluation. These techniques should be of interest to planning practitioners working on knowledge-rich application domains. Another emerging use of these techniques is the semantic web, where current ontology languages based on description logics need to be extended to reason about goals and capabilities for web services and agents.


Data Integration

AI Magazine

Data integration is the problem of combining data residing at different autonomous, heterogeneous sources and providing the client with a unified, reconciled global view of the data. We discuss dataintegration systems, taking the abstract viewpoint that the global view is an ontology expressed in a class-based formalism. We resort to an expressive description logic, ALCQI, that fully captures classbased representation formalisms, and we show that query answering in data integration, as well as all other relevant reasoning tasks, is decidable. However, when we have to deal with large amounts of data, the high computational complexity in the size of the data makes the use of a fullfledged expressive description logic infeasible in practice. This leads us to consider DL-Lite, a specifically tailored restriction of ALCQI that ensures tractability of query answering in data integration while keeping enough expressive power to capture the most relevant features of class-based formalisms.


The Description Logic Handbook

AITopics Original Links

Description logics are embodied in several knowledge-based systems and are used to develop various real-life applications. Now in paperback, The Description Logic Handbook provides a thorough account of the subject, covering all aspects of research in this field, namely: theory, implementation, and applications. Its appeal will be broad, ranging from more theoretically oriented readers, to those with more practically oriented interests who need a sound and modern understanding of knowledge representation systems based on description logics. As well as general revision throughout the book, this new edition presents a new chapter on ontology languages for the semantic web, an area of great importance for the future development of the web. In sum, the book will serve as a unique resource for the subject, and can also be used for self-study or as a reference for knowledge representation and artificial intelligence courses.


Description Logics Courses and Tutorials

AITopics Original Links

Enrico Franconi's Course on Description Logics The material includes slides for 6 modules ( 320 slides): A review of Computational Logics, Structural Description Logics, Propositional Description Logics, Description Logics and Knowledge Bases, Description Logics and Logics, Description Logics and Databases. A web pointer to an online modified version of CRACK, allowing for tracing satisfiability proofs with tableaux, is provided. Pointers to relevant online literature are provided, too. Enrico Franconi's Course on Description Logics The material includes slides for 6 modules ( 320 slides): A review of Computational Logics, Structural Description Logics, Propositional Description Logics, Description Logics and Knowledge Bases, Description Logics and Logics, Description Logics and Databases. A web pointer to an online modified version of CRACK, allowing for tracing satisfiability proofs with tableaux, is provided.



Zhiqiang Zhuang, Zhe Wang, Kewen Wang and Guilin Qi (2016) DL-Lite Contraction and Revision

#artificialintelligence

Two essential tasks in managing description logic knowledge bases are eliminating problematic axioms and incorporating newly formed ones. Standard description logic semantics yields an infinite number of models for DL-Lite knowledge bases, thus it is difficult to develop algorithms for contraction and revision that involve DL models. It is more succinct and importantly, with a finite signature, the semantics always yields a finite number of models. We then define model-based contraction and revision functions for DL-Lite knowledge bases under type semantics and provide representation theorems for them.


Description Logics and Planning

AI Magazine

This article surveys previous work on combining planning techniques with expressive representations of knowledge in description logics to reason about tasks, plans, and goals. Description logics can reason about the logical definition of a class and automatically infer class-subclass subsumption relations as well as classify instances into classes based on their definitions. Descriptions of actions, plans, and goals can be exploited during plan generation, plan recognition, or plan evaluation. Another emerging use of these techniques is the semantic web, where current ontology languages based on description logics need to be extended to reason about goals and capabilities for web services and agents.


Second KL-One Workshop

AI Magazine

The second KL-One workshop was held over a five-day period in October, 1981. The workshop included a general conference session, wherein people could report on activies at their own institutions, and a two day working research session.