Schedule
Literature
Handouts
Exercises
Revision
Assessment

COMP304 & COMP521: Knowledge Representation and Reasoning
Wiebe van der Hoek
Department of Computer Science
University of Liverpool
Liverpool L69 7ZF, UK
email wiebe@csc.liv.ac.uk
tel (+44 151) 794 3672/7480
fax (+44 151) 794 3715
Schedule
You can find the time table for the course on the Orbit system.You can also find it in the first copies of the handouts (see below).
The course starts on Monday 28th of September. Thus: week 1 of the course
corresponds to week 40 of the year.
You find here the syllabus for COMP521 and here the syllabus for COMP304.
There will be two classtests during this term (each of
one hour) and an exam (two and a half hours). See also
assessment. The specific requirements and specifications for each of the two class tests are here.
The schedule for the class tests is as follows:

The first class test takes place Friday 6 November, at the usual lecture time (13:00) and venue (Jane Herdman).
The marks for this class test are here.

The second class test will take place in December.
A mock test is available here.
Literature
There is no compulsory literature to be read for
the course. Here are some hints for those who like to
know more.
The course basically deals with Description Logic and
with Modal Logic, with Epistemic Logic as the main
application in the second half of the course.
The following book provides background information for Modal
and Epistemic Logic. Ten copies of it are available in the library. All references in the descriptions of the week refer to this book.
Epistemic Logic for AI and Computer Science
J.J.Ch. Meyer and W. van der Hoek
Cambridge Tracts in Theoretical Computer Science 41, 1995.
As far as description logics are concerned, you can have a look at
Reasoning and Revision in Hybrid Representation Systems
Bernhard Nebel
Lecture Notes in Artificial Intelligence 422
SpringerVerlag, 1990
This book is out of print, but available for download. There is also the following book
Logic in Computer Science: Modelling and Reasoning about Systems
M. Huth and M. Ryan
Cambridge University Press, 2000
which gives an overview of applications of modal and related logics (the Harold Cohen Library has three copies, class no. 518.54.H97)
Handouts and Schedule
The handouts contain several slides per page. They will also
be distributed at each first lecture to which they apply!
 Week 1, starting 28 September.
Introduction to knowledge representation (KR), formalisms for KR and in particular propositional logic, introduction to modal logic.
The first set of handouts are
here.
 Week 2, 3 and 4.
Modal logic.
Here are the handouts.
 Week 5, 6 and 7.
Description Logic.
Here are the handouts.
 Week 8, 9, and 10.
Epistemic Logic.
Here are the handouts, and
here are the handouts in a oneperpage format.—>
 Week 10 and 11.
Basic Probability Theory.
Here and here are the two sets of handouts.
Exercises
They are to be found in the
handouts above.
Revision

As a preparation for each of the two class tests, a mock test will be handed out during the lectures and discussed at the tutorials.
 This is the first mock test
 This is the second mock test
Assessment
 Weightings:
 12.5% class test 1
 12.5% class test 2
 75% written examination about all the material covered in the lecture, the tutorial and the handouts
 Failure in one of the tasks cannot be compensated for by another task.

Class test 1's Learning Outcomes:
 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
 Class test 2's Learning Outcomes:
 be able to perform inference tasks in description logic
 be able to use tableau based methods to do inference in description logic.
 Exam's Learning Outcomes:
 All learning outcomes for COMP304 and
COMP521.
Syllabus
Level: 3 (COMP304) and M (COMP521)
Semester: 1
Credits: 15
Department: CS
Student contact: 46 hours
Delivery: 32 lectures, 10 Tutorials
Prerequisites: COMP210
Corequisites: None
Preliminary reading: None
Proposed  Subject to Approval
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
Learning outcomes:
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;

be able to perform simple Hilbertstyle deductions in modal and epistemic logic;

be able to use tableau based methods to do inference in description logic.
Recommended texts:
see Literature
