Knowledge Representation and Inference (U02495)

? Credit Points : 10 ? SCQF Level : 9 ? Acronym : INF-3-KRI

The aim of this course is to teach the fundamentals of representing knowledge within a computer and of drawing inferences automatically from this knowledge. It builds on the introductions to propositional and first-order logic taught in Informatics 1 and 2, and extends these to representing time, belief, qualitative knowledge, etc, and or reasoning using constraints, learning and making conjectures, which are needed by automated agents that reason about the world and other agents. It will provide many of the prerequisites for later courses in knowledge-based and agent-based computation.

Entry Requirements

? Pre-requisites : Informatics 2B Informatics 2D Successful completion of Year 2 of an Informatics Single or Combined Degree, or equivalent by permission of the School.

Subject Areas

Home subject area

Knowledge Representation and Reasoning, (School of Informatics, Schedule O)

Delivery Information

? Normal year taken : 3rd 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
09/01/2007	16:10	17:00			Room A9/11, Forrest Hill

All of the following classes

Type	Day	Start	End	Area
Lecture	Tuesday	16:10	17:00	Central
Lecture	Friday	16:10	17:00	Central

Summary of Intended Learning Outcomes

On completion of the course, students should be able to:
1. Understand the scope and limitations of the various knowledge representation and inference techniques they have studied.
2. Demonstrate their understanding of knowledge representation techniques by representing time, belief, conjecture, constraints to represent common-sense knowledge, and by explaining their design decisions.
3. Demonstrate their understanding of inference techniques by successfully using an inference engine automatically to infer new knowledge from old via deduction, conjecture or learning.