Knowledge Representation and the Semantic Web 7,5 Credits
Course Contents
Knowledge representation and reasoning (KR) is an established area in Artificial Intelligence (AI) since the 1960s. It deals with explicit, symbolic, declarative representations of knowledge and inference procedures for deriving further and implicit information from these representations. It remains crucial for the overall development of AI. Although recent developments in statistical approaches and machine learning have been very successful, limitations of these methods are apparent. It is believed that some of these limitations can only be overcome with advances in knowledge representation. This course aims to introduce students to various topics in KR. The course covers both fundamental principles and recent advancements in the field, including those developed from the area of the Semantic Web, whose backbone is based on theories and methods built in knowledge representation.The course includes the following elements:
- Description Logics
- Ontology and Ontology Engineering
- Knowledge Graphs
- Standard Semantic Web technologies
- Answer-Set Programming and reasoning about actions and change
Prerequisites
The applicant must hold the minimum of a bachelor’s degree (i.e the equivalent of 180 ECTS credits at an accredited university) with at least 90 credits in Computer Engineering, Computer Science or Electrical Engineering (with relevant courses in computer engineering), or equivalent, or passed courses at least 150 credits from the programme Computer Science and Engineering. The bachelor’s degree should comprise a minimum of 15 credits in mathematics. Proof of English proficiency is required.Level of Education: Master
Course code/Ladok code: TSWR21
The course is conducted at: School of Engineering
