COMP304 & COMP521: Knowledge Representation and Reasoning

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 class-tests 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.

As far as description logics are concerned, you can have a look at

This book is out of print, but available for download. There is also the following book

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

1. 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.
   
2. Week 2, 3 and 4.
   Modal logic.
   Here are the handouts.
   
3. Week 5, 6 and 7.
   Description Logic.
   Here are the handouts.
   
4. Week 8, 9, and 10.
   Epistemic Logic.
   Here are the handouts, and here are the handouts in a one-per-page format.—>
   
5. Week 10 and 11.
   Basic Probability Theory. Here and here are the two sets of handouts.
   

Exercises

Revision

1. 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:
  1. 12.5% class test 1
  2. 12.5% class test 2
  3. 75% written examination about all the material covered in the lecture, the tutorial and the handouts
  4. Failure in one of the tasks cannot be compensated for by another task.
• Class test 1's Learning Outcomes:
  1. 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;
  2. be able to demonstrate knowledge of the basics of propositional logic
  3. be able to determine the truth/satisfiability of modal formula;
  4. be able to perform modal logic model checking on simple examples
• Class test 2's Learning Outcomes:
  1. be able to perform inference tasks in description logic
  2. be able to use tableau based methods to do inference in description logic.
• Exam's Learning Outcomes:
  1. All learning outcomes for COMP304 and COMP521.

Syllabus

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:

• 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 Hilbert-style deductions in modal and epistemic logic;
• be able to use tableau based methods to do inference in description logic.

Recommended texts: