University of Malta DEPARTMENT OF
COMPUTER SCIENCE AND AI

PROBLEM SOLVING METHODS
IN ARTIFICIAL INTELLIGENCE

COURSE DESCRIPTION


Credits 2
Lectures 20 (approx.)
Tutorials/Practicals 8 (approx.)
Assessment Test: 85%; Coursework 15%
Leads To cs305: Natural Language Processing; 
cs307: Machine Learning and Automated Reasoning. 
Prerequisites csi107: Logic and Logic Programming
Lecturer Michael Rosner

Course Objectives

This unit focuses on the relation between problem-solving techniques in the areas of search, reasoning, and planning, and programming techniques. The lingua franca of the course will be Prolog, and where necessary, some lectures will be devoted to reviewing the main ideas behind the language.

Course Contents and Organisation

The table below gives an indication of resources allocated to each of the above areas subdivided by topic.

Area

Topics

Lectures
1. AI Programming
  • Prolog Language
  • Agenda Based Search
  • Meta Interpretation
    • 5
    2. Search
  • Basic Search Techniques
  • Game Playing* 
  • Constraint Satisfaction Problems
    		•
    5
    3. Reasoning
  • Rule Based Inference 
  • Temporal Reasoning*
    		•
    5
    4. Planning
  • Linear Planning
  • Partial Order Planning
    		•
    5
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    Last modified: Fri Feb 5 18:03:07 1999