Knowledge Representation and Reasoning

      -- Logic meets Probability Theory --


      Latest News
      • Deadline asssignment II: 6th January, 2012
      • Lecture notes and solutions to exercises are now available! (see below)
      • No practical assistance any more. You are expected to work on the two assignments on an individual basis (as these determine 50% of the mark you get). However, if you get stuck with either Prolog or AILog we are happy to help you. Simply drop us an email, or make an appointment
      • Final mark = 50% exam + 50% practical
      • Exam: 16th January, 2012, 10:30-12:30, room Huygens HG00.304
      • Mock exam
      • Marks for exam 16/1/2012
      • Submission of assignments: through blackboard


      Knowledge representation and Reasoning is an AI course where we systematically study representation and reasoning methods with logic and probability theory as the canonical forms. In the end we show that 'never the twain shall meet' is no longer true in recent AI.

      Preliminary Content of Lectures in 2011:

      The lectures constitute the backbone of the course. You need to understand (and not simply be able to reproduce) the content of the slides to pass the exam.
      • Lecture 1: Introduction (5th September, 2011) [Slides 1/page: PDF]
        Content of course, learning aims. Connection between cognition and knowledge representation. Requirements for knowledge-representation languages.

      • Lecture 2: Revision of logic in AI (12th September, 2011) [Slides 1/page: PDF]
        See Appendix A, lecture notes
        Required background knowledge of logic needed in the course. Start reading these notes in the week of 5th September, 2011. You need to have read this until page 102!

      • Lecture 3 and 4: Logic Programming, Prolog (19th September, 2011) [Slides 1/page: PDF, or 6/page: Gzipped Postscript
        Prolog and AILog (26th September, 2011) [Slides 1/page PDF: Overview AILog]
        Small AILog knowledge base on cardiology (Note mime type is ail)
        There is a close connection between knowledge representation, logic programming and Prolog. Logic programming is also the foundation for much recent work on relational learning. Covered are the basics of logic programming, Prologs and the AILog system. AILog is a knowledge representation and reasoning system based on Horn clause logic and probability theory. It will be used in two subsequent assigments for which you get a mark.

      • Lecture 5: Description logics and Frames (3rd October, 2011) [Slides 1/page: PDF]
        In recent years, partly due to the world-wide web, has seen an increasing interest in representing and reasoning with things that exist in the real world using special purpose logics.

      • Lecture 6: Model-based reasoning (10th October, 2011) [Slides 1/page: PDF]
        Model-based reasoning is a separate research area in AI with a focus on trouble shooting and diagnosis. This lecture focuses on the use of models of normal behaviour for diagnosis

      • Lecture 7: Model-based reasoning (continued) (17th October, 2011) [Slides 1/page: PDF]
        This lecture looks at using knowledge of abnormal behaviour, expressed as causal knowledge, for diagnosis using a reasoning method, called abduction (= reasoning to the best explanation)
        AUTUMN BREAK 24th October-4th November, 2011

      • Lecture 8: Uncertainty reasoning I (7th November, 2011) [Slides 1/page: PDF]

      • Lecture 9: Uncertainty reasoning II (14th November, 2011) [Slides 1/page: PDF]

      • Lecture 10: Uncertainty reasoning III (21st November, 2011; cancelled, see slides lecture 9)

      • Lecture 11: Decision Making (28th November, 2011) [Slides 1/page: PDF]

      • Lecture 12: Probabilistic logic (5th December, 2011) [Slides 1/page: PDF]

      Lectures Notes:

      • Lecture notes used in the course. These complement the slides and tutorial exercises. (You may bring the lecture notes together with the slides and your own lecture notes to the exam. Note that you are not allowed to bring the tutorial exercises to the exam.)

      Content of Practicals:

      Aim of the practical is to get you quickly familiar of the basics of logic programming, Prolog and AILog. You will need this understanding for the two assignments.
      • Prolog and AILog Practical manual [PDF]

      • SWI Prolog

      • Prolog and AILog exercises

      • AILog manual

      • AIlog system

      Assignments:

      There are two assignments

      • Practical assignment I: deadline 15th December, 2011

      • Practical assignment II: deadline 6th January, 2012

      • AIlog system

      Tutorials:

      The tutorials complement the lectures and are meant for you to check your understanding ot the material covered by the lectures.
      • Tutorial on 15th September, 2011 [Exercises PDF]

      • Tutorial on 6th October, 2011 on Description logics and frames [Exercises PDF]

      • Tutorial on 13th and 20th October, 2011 on Model-based reasoning [Exercises PDF]

      • Tutorial on 10th, 17th November and 1st December, 2011: Reasoning with uncertainty [Exercises PDF]

      • Solutions to the exercises



      Peter Lucas | Computing Science
      Radboud University Nijmegen

      Last updated: 4th September, 2011
      peterl AT cs.ru.nl