This document provides an introduction to description logics, which are a family of logics concerned with knowledge representation. Description logics allow structuring knowledge through concepts, relationships, and axioms. They provide a decidable fragment of first-order logic with automated reasoning procedures. The document discusses key description logics like ALC, constructors, formal semantics, terminological and assertion boxes, logical implication, and reasoning services like concept satisfiability, subsumption, and instance checking. It also covers extensions like cardinality restrictions and individuals.
Artificial Intelligence (AI) | Prepositional logic (PL)and first order predic...Ashish Duggal
The following are the topics in this presentation Prepositional Logic (PL) and First-order Predicate Logic (FOPL) is used for knowledge representation in artificial intelligence (AI).
There are also sub-topics in this presentation like logical connective, atomic sentence, complex sentence, and quantifiers.
This PPT is very helpful for Computer science and Computer Engineer
(B.C.A., M.C.A., B.TECH. , M.TECH.)
Richardson Eyres - Three Peaks Challenge Competition Richardson Eyres
Richardson Eyres are delighted to announce that we have completed the three peaks challenge in aid of Helen and Douglas House; our local hospice for children and young adults.
These are some of the pictures we took during the challenge.
Artificial Intelligence (AI) | Prepositional logic (PL)and first order predic...Ashish Duggal
The following are the topics in this presentation Prepositional Logic (PL) and First-order Predicate Logic (FOPL) is used for knowledge representation in artificial intelligence (AI).
There are also sub-topics in this presentation like logical connective, atomic sentence, complex sentence, and quantifiers.
This PPT is very helpful for Computer science and Computer Engineer
(B.C.A., M.C.A., B.TECH. , M.TECH.)
Richardson Eyres - Three Peaks Challenge Competition Richardson Eyres
Richardson Eyres are delighted to announce that we have completed the three peaks challenge in aid of Helen and Douglas House; our local hospice for children and young adults.
These are some of the pictures we took during the challenge.
Lecture slides by Mustafa Jarrar at Birzeit University, Palestine.
See the course webpage at: http://jarrar-courses.blogspot.com/2011/12/description-logic.html
The lecture covers: Description Logic & Business Rules, In Artificial Intelligence Course, Birzeit University, Spring 2013
Semantic Web technologies are a set of languages standardized by the World Wide Web Consortium (W3C) and designed to create a web of data that can be processed by machines. One of the core languages of the Semantic Web is Web Ontology Language (OWL), a family of knowledge representation languages for authoring ontologies or knowledge bases. The newest OWL is based on Description Logics (DL), a family of logics that are decidable fragments of first-order logic. leanCoR is a new description logic reasoner designed for experimenting with the new connection method algorithms and optimization techniques for DL. leanCoR is an extension of leanCoP, a compact automated theorem prover for classical first-order logic.
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Macroeconomics- Movie Location
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How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
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Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
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Jarrar.lecture notes.aai.2011s.descriptionlogic
1. Dr. Mustafa Jarrar [email_address] www.jarrar.info University of Birzeit Description Logic (and business rules) Advanced Artificial Intelligence (SCOM7341) Lecture Notes, Advanced Artificial Intelligence (SCOM7341) University of Birzeit 2 nd Semester, 2011
2. Reading Material D. Nardi, R. J. Brachman. An Introduction to Description Logics . In the Description Logic Handbook, edited by F. Baader, D. Calvanese, D.L. McGuinness, D. Nardi, P.F. Patel-Schneider, Cambridge University Press, 2002, pages 5-44. http://www.inf.unibz.it/~franconi/dl/course/dlhb/dlhb-01.pdf Only Sections 2.1 and 2.2 are required (= the first 32 pages)
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7. Description logic ALC (Syntax and Semantic) Woman ⊑ Person ⊓ Female Parent ⊑ Person ⊓ hasChild. ⊤ Man ⊑ Person ⊓ Female NotParent ⊑ Person ⊓ hasChild. ⊥ Examples: Constructor Syntax Semantics Primitive concept A A I I Primitive role R R I I I Top ⊤ I Bottom ⊥ Complement C I C I Conjunction C ⊓ D C I D I Disjunction C ⊔ D C I D I Universal quantifier R.C { x | y . R I ( x , y ) C I ( y )} Extensional quantifier R.C { x | y . R I ( x , y ) C I ( y )}
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19. Some extensions of ALC Constructor Syntax Semantics Primitive concept A A I I Primitive role R R I I I Top ⊤ I Bottom ⊥ Complement C I C I Conjunction C ⊓ D C I D I Disjunction C ⊔ D C I D I Universal quantifier R.C { x | y . R I ( x , y ) C I ( y )} Extensional quantifier R.C { x | y . R I ( x , y ) C I ( y )}
20. Some extensions of ALC Constructor Syntax Semantics Primitive concept A A I I Primitive role R R I I I Top ⊤ I Bottom ⊥ Complement C I C I Conjunction C ⊓ D C I D I Disjunction C ⊔ D C I D I Universal quantifier R.C { x | y . R I ( x , y ) C I ( y )} Extensional quantifier R.C { x | y . R I ( x , y ) C I ( y )} Cardinality ( N ) ≥ n R { x | #{ y | R I ( x , y ) } ≥ n } ≤ n R { x | #{ y | R I ( x , y ) } ≥ n } Qual. cardinality ( Q ) ≥ n R.C { x | #{ y | R I ( x , y ) C I ( y )} ≥ n } ≤ n R.C { x | #{ y | R I ( x , y ) C I ( y )} ≥ n } Enumeration ( O ) { a 1 … a n } { a I 1 … a I n } Selection ( F ) f : C { x Dom( f I ) | C I ( f I ( x ))}
36. UML Class diagram (with a contradiction and an implication) Student ⊑ Person PhDStudent ⊑ Person Employee ⊑ Person PhD Student ⊑ Student ⊓ Employee Student ⊓ Employee ≐ ⊥ {disjoint} Person Student Employee PhD Student
37. Infinite Domain: the democratic company [Franconi 2007] Supervisor ⊑ =2 Supervises.Employee Employee ⊑ Supervisor Supervises 2..2 0..1 implies “ the classes Employee and Supervisor necessarily contain an infinite number of instances”. Since legal world descriptions are finite possible worlds satisfying the constraints imposed by the conceptual schema, the schema is inconsistent . Supervisor Employee
38. Example (in UML, EER and ORM) Employee Project WorksFor TopManager Manages Employee Project WorksFor Manages 1..1 1..1 TopManger WorksFor Manages Project TopManger Employee 1..1 1..1