Module Specification

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.
1. Module Title Knowledge Representation
2. Module Code COMP521
3. Year Session 2023-24
4. Originating Department Computer Science
5. Faculty Fac of Science & Engineering
6. Semester First Semester
7. CATS Level Level 7 FHEQ
8. CATS Value 15
9. Member of staff with responsibility for the module
Dr LB Kuijer Computer Science Louwe.Kuijer@liverpool.ac.uk
10. Module Moderator
11. Other Contributing Departments  
12. Other Staff Teaching on this Module
Mrs J Birtall School of Electrical Engineering, Electronics and Computer Science Judith.Birtall@liverpool.ac.uk
13. Board of Studies
14. Mode of Delivery
15. Location Main Liverpool City Campus
    Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
16. Study Hours 30

  10

    5

45
17.

Private Study

105
18.

TOTAL HOURS

150
 
    Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other
19. Timetable (if known)            
 
20. Pre-requisites before taking this module (other modules and/or general educational/academic requirements):

 
21. Modules for which this module is a pre-requisite:

 
22. Co-requisite modules:

 
23. Linked Modules:

 
24. Programme(s) (including Year of Study) to which this module is available on a mandatory basis:

25. Programme(s) (including Year of Study) to which this module is available on a required basis:

26. Programme(s) (including Year of Study) to which this module is available on an optional basis:

27. Aims
 

To introduce Knowledge Representation as a research area.
To give a complete and critical understanding of the notion of representation languages and logics.
To study modal logics and their use.
To study description logic and its use.
To study epistemic logic and its use.
To study methods for reasoning under uncertainty

 
28. Learning Outcomes
 

(LO1) Demonstrate a critical understanding of the languages of modal and description logics by translating between English and those languages.

 

(LO2) Exhibit a comprehensive understanding of the semantics of modal and description logics by arguing whether formulas of propositional, modal and description logic are true or valid.

 

(LO3) Analyse scenarios involving knowledge, and represent them in modal and description logics.

 

(LO4) Have a deep understanding of formal proof methods and apply them to modal and description logics.

 

(S1) Problem Identification

 

(S2) Critical Analysis

 

(S3) Solution Synthesis

 

(S4) Evaluation of Problems and Solutions

 
29. Teaching and Learning Strategies
 

Teaching Method 1 - Lecture
Description:
Attendance Recorded: Not yet decided

Teaching Method 2 - Tutorial
Description:
Attendance Recorded: Not yet decided

Teaching Method 3 - Assessment
Description:
Attendance Recorded: Not yet decided
Notes: One exam and two class tests

Standard on-campus delivery
Teaching Method 1 - Lecture
Description: Mix of on-campus/on-line synchronous/asynchronous sessions
Teaching Method 2 - Tutorial
Description: On-campus synchronous sessions

 
30. Syllabus
   

Introduction to knowledge representation (KR), formalisms for KR and in particular propositional logic (1 week).
Introduction to modal and description logics (5 weeks): Modal logics: Syntax, semantics (Kripke models), model checking, theorem proving. Description logics: Syntax, semantics, satisfiability checking, expressive description logics.
Applications of modal logic: epistemic logic (3 weeks): One agent case: S5 models, specific properties; Multi-agent case: Modelling epistemic puzzles, reasoning about other's knowledge and ignorance, alternating bit protocols; Group notions of knowledge: Distributed knowledge, common knowledge,examples; Computational models: Interpreted systems.
Handling uncertain information through probability and decision theory (2 weeks): Sample spaces; independence; conditional probability; prior and posterior probabilities; random variables; decision theory for agent systems; Bayesian networks.

 
31. Recommended Texts
  Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.
 

Assessment

32. EXAM Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
  (521) Final Exam There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :Semester 1 150 75
33. CONTINUOUS Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
  (521.1) Class Test 1 There is a resit opportunity. Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Around week 5 0 13
  (521.2) Class Test 2 There is a resit opportunity. Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Around week 10 0 12