Multi-agent Semantic Web Systems (Level 10) (U02227)

? Credit Points : 10 ? SCQF Level : 10 ? Acronym : INF-4-MASWS

The aim of the course is to give students an understanding of the theory and practice of large-scale, knowledge-based systems operating in an open, distributed environment. The primary intended examples of such systems are the Semantic Web; the semantic layer of grid based systems; and the coordination aspects of open multi-agent systems.

Entry Requirements

? Pre-requisites : Successful completion of Year 3 of an Informatics Single or Combined Honours Degree, or equivalent by permission of the School. Students should have a basic familiarity with the syntax and semantics of first order logic.

? Prohibited combinations : Multi-agent Semantic Web Systems (Level 11)

Subject Areas

Home subject area

Artificial Intelligence, (School of Informatics, Schedule O)

Other subject areas

Cognitive Science, (School of Informatics, Schedule O)

Net-Centric Computing, (School of Informatics, Schedule O)

Computational Linguistics, (School of Informatics, Schedule O)

Delivery Information

? Normal year taken : 4th year

? Delivery Period : Semester 2 (Blocks 3-4)

? Contact Teaching Time : 2 hour(s) per week for 10 weeks

First Class Information

Date	Start	End	Room	Area	Additional Information
12/01/2009	12:10	13:00	Room 4.12, Appleton Tower	Central

All of the following classes

Type	Day	Start	End	Area
Lecture	Monday	12:10	13:00	Central
Lecture	Thursday	12:10	13:00	Central

Summary of Intended Learning Outcomes

On completion of the course, students should be able to:
1. Show an understanding of the basic principles of different theoretical models of distributed knowledge-based systems, and assess their applicability to specific knowledge-sharing tasks.
2. Describe the motivations for, and effectiveness of, inference and planning techniques in the implementation of distributed knowledge-based systems.
3. Critically assess the adequacy of relevant standards (WSDL, RDF, OWL, etc) as a basis for building practical systems.
4. Demonstrate an understanding of how the architecture and design of distributed knowledge-based systems interacts with wider social and technological developments.