Module Details |
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module. |
Title | KNOWLEDGE REPRESENTATION | ||
Code | COMP521 | ||
Coordinator |
Dr D Kuijer Computer Science Louwe.Kuijer@liverpool.ac.uk |
||
Year | CATS Level | Semester | CATS Value |
Session 2016-17 | Level 7 FHEQ | First Semester | 15 |
Aims |
|
This module aims:
|
Learning Outcomes |
|
The module addresses learning outcomes 2, 3, 4, 5 and 6 for the MSc in Computer Science programme, and learning outcomes 2, 3, 4, 5 and 6 for the MEng in Computer Science programme. At the end of the module, the student will be able to explain and discuss the need for formal approaches to knowledge representation in artificial intelligence, and in particular the value of logic as such an approach; |
|
be able to demonstrate knowledge of the basics of propositional logic; |
|
be able to determine the truth/satisfiability of modal formula; |
|
be able to perform modal logic model checking on simple examples; |
|
be able to perform inference tasks in description logic; |
|
be able to model problems concenring agents'' knowledge using epistemic logic; |
|
be able to indicate how updates and other epistemic actions determine changes on epistemic models; |
|
have sufficient knowledge to build "interpreted systems" from a specification, and to verify the "knowledge" properties of such systems; |
|
be familiar with the axioms of a logic for knowledge of multiple agents; |
|
be able to demonstrate knowledge of the basics of probability and decision theory, and their use in addressing problems in knowledge representation; |
|
be able to model simple problems involving uncertainty, using probability and decision theory; |
|
able to perform simple Hilbert-style deductions in modal and epistemic logic; |
|
able to use tableau based methods to do inference in description logic. |
Syllabus |
|
1 |
|
Teaching and Learning Strategies |
|
Lecture - |
|
Tutorial - |
|
Assessment - One exam and two class tests |
Teaching Schedule |
Lectures | Seminars | Tutorials | Lab Practicals | Fieldwork Placement | Other | TOTAL | |
Study Hours |
30 |
10 |
5 |
45 | |||
Timetable (if known) |
One exam and two class tests
|
||||||
Private Study | 105 | ||||||
TOTAL HOURS | 150 |
Assessment |
||||||
EXAM | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
Unseen Written Exam | 150 | Semester 1 | 75 | Yes | Standard UoL penalty applies | Final Exam Notes (applying to all assessments) Two assessment tasks This work is not marked anonymously. Written examination |
CONTINUOUS | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
Coursework | 1 hour for all CAs | 1 | 12.5 | Yes | Standard UoL penalty applies | Assessment 1 |
Coursework | 1 hour for all CAs | Semester 1 | 12.5 | Yes | Standard UoL penalty applies | Assessment 2 |
Recommended Texts |
|
Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module. Explanation of Reading List: |