Artificial Intelligence 1

The course is a substitute for:

Artificial Intelligence 1 (XE33UI1)

Lecturer:

Tutor:

Supervisor:

Department of Cybernetics

Synopsis:

The course covers those AI topics which are either closely bound to a declarative programming language Prolog or which can be well presented within this context. First, there are explained principles of Prolog - a language designed for AI problem solving. Characteristic programming methodogy is introduced using specific solutions of typical AI problems (state-space search, simple expert system, etc.).

Special attention is given to AI methods developed for communication with a computer in (written) natural language and to methods of common sense reasoning. Inductive logic programming will be introduced as a new perspective method extending significantly application possibilies of machine learning.

Requirements:

Syllabus of lectures:

1. Programming tools for AI and their requested properties

2. Principles of declarative programming languages. Logic programming and proof by resolution

3. Principles of Prolog

4. State space search and Prolog

5. Review of Prolog solutions for characteristic AI problems. Typical applications

6. New dicections in logic programming. Constraint logic programming (CLP)

7. Utilisation of natural language communication within AI systems. Phases of natural languege processing

8. Role of syntax and semantics of a sentence. DCG grammars

9. Design of a module for natural language communication. Imortance of implicit informations. State space search methods and their complexity

10. Common sense reasoning and its partial automation. Naive physics

11. Qualitative simulation

12. Background knowledge and its role in inductive logic programming (ILP)

13. Principles of ILP systems, review of properties of used training examples

14. Practical applications of ILP

Syllabus of tutorials:

1. Programming language Prolog and its philosophy

2. Facts, rules, queries. List and basic operations on them

3. Negation in Prolog. Implemention of various types of search

4. Hands on excercises with more complex tasks in Prolog I

5. Grammars in Prolog

6. Hands on excercises with more complex tasks in Prolog II

7. Hands on excercises with more complex tasks in Prolog III

8. CLP system Eclipse demonstration

9. Natural language processing in Prolog

10. Implementation of a question-answering systém

11. Common sense reasoning and naive physics

12. System QUASIMODO - hands on excercises

13. Introduction of an ILP system FOIL

14. Hands on excercises with FOIL

Study Objective:

Study materials:

(1) Russell, S., Norvig, P.: Artificial Intelligence, A Modern Approach. Prentice Hall Series in AI, Englewood Cliffs, New Jersey 1995

(2) Bratko, I.: Prolog Programming for All. Reading, Addison Wesley 1991, 2nd edition

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans: