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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 Page 1 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/ Page 2 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 Page 3