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COMP703: Artificial Intelligence
Genetic Programming
1.
General
Lecturer:
Nelishia Pillay
Contact Details:
Tel: 2605644
E-mail: [email protected]
Web Page URL:
http://titan.cs.unp.ac.za/~nelishiap/
2.
Introduction
This course provides an in-depth study of the field of genetic programming. The foundations
of genetic programming lie in genetic algorithms and hence in Darwins theory of evolution.
Given a description of a problem domain, a genetic programming system induces an
algorithm to solve the problem.
Syllabus
•
Introductory Concepts Overall Algorithm, Representation, Control Models ,Genetic
Operators, Selection Methods, Fitness Functions.
•
Applications of Genetic Programming: Symbolic Regression, Classification Problems,
Game Playing, Blocks World and more.
•
Advanced Features: Memory usage, Modularization, Strongly-Typed GP,
Architecture-Altering Operators.
•
Problems: Destructive Effects of Operators, Introns and Bloat, Premature
Convergence.
3.
Assessment
Assessment for this course will be continuous. The assessment is comprised of two tests
and three assignments. The final mark obtained for the course will be calculated as follows:
Final mark = 0.5 x (average obtained for assignments) + 0.5 x (average obtained for tests)
4.
Test Dates
Date
Duration
Test 1
28 March
1 hr 30 mins
Test 2
16 May
1 hr 30 mins
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5.
Submission of Assignments
E-Mail assignments (reports and program files) to [email protected] on or before the
due date. Assignment due dates:
Due Date
6.
Assignment 1: Part 1
21 February
Assignment 1: Part 2
28 February
Assignment 1: Part 3
7 March
Assignment 1: Part 4
21 March
Assignment 2
11 April
Assignment 3
9 May
Resources
Books
1.
Banzhaf W., Nordin P., Keller R.E., Francone F.D., Genetic Programming - An
Introduction - On the Automatic Evolution of Computer Programs and its
Applications, Morgan Kaufmann Publishers, Inc., 1998.
2.
Koza J. R., Genetic Programming I : On the Programming of Computers by Means of
Natural Selection - John R. Koza, MIT Press,1992.
3.
Koza J.R., Genetic Programming II, Automatic Discovery of Reusable Programs, MIT
Press, 1994.
4.
Koza J.R.,Bennett III F.H.,Andre D., Keane M.A., Genetic Programming III, Darwinian
Invention and Problem Solving, Morgan Kaufmann Publishers, 1999.
5.
Poli, R., Langdon, W.B., MCPhee, N.F., Koza, J.R., A Field Guide to Genetic
Programming, 2008, http://www.gp-field-guide.org.uk/
Websites
1.
http://www.gp-field-guide.org.uk/
2.
http://www.cs.nott.ac.uk/~smg/biblio/
3.
http://www.cs.bham.ac.uk/~wbl/biblio/
4.
http://liinwww.ira.uka.de/bibliography/Ai/genetic.programming.html
5.
Tiny-GP - http://cswww.essex.ac.uk/staff/rpoli/TinyGP/
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Course Schedule
Week
Topic
Week 1:
10 – 14 Feb
Genetic algorithm Example, An Introduction to Genetic Programming, Control
Models, Initial Population Generation
Week 2:
17 – 21 Feb
Evaluation, Selection Methods, Genetic Operators
Week 3:
24 - 28 Feb
Genetic operators, Reporting on Results Obtained by Genetic Programming
Systems
Week 4:
3-7 Mar
Week 5:
Assignment 1, Part 1 due
Assignment 1, Part 2 due
Symbolic Regression Problems
Assignment 1, Part 3 due
Classification Problems
10 –14 Mar
Week 6:
17 – 21 Mar
19 March - Friday's Timetable
Using Iterative Control Structures, An Introduction to the Blocks World Problem
Assignment 1, Part 4 due
Week 6:
Test 1
24 – 28 Mar
Week 7:
31 Mar - 4 Apr
Test 1 Feedback
Evolving Recursive Algorithms
Week 8:
7 – 11 Apr
Evolving Game Playing Strategies
Assignment 2 due
13 -18 Apr
EASTER VACATION
Week 9:
14-18 Apr
Evolving Modular Programs - Module Acquisition, Evolving Modular Programs Automatically Defined Functions
Week 10:
21 – 25 Apr
Evolving Algorithms that Use Memory, Data Structures
Week 11:
28 Apr – 2 May
Architecture-Altering Operators
Week 12:
5 – 9 May
Limitations of Genetic Programming
Week 13:
Test 2
Assignment 3 due
12 -16 May
Week 14:
19 – 23 May
Test 2 feedback
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