====== Lab exercises ====== ===== Programme ===== The order or the contents of the labs can change! | 21.09. | 1. | L | Successful applications of EAs (lecture in the time of lab exercise) | | | 28.09. | 2. | S | **Cancelled. Holiday.** | | | 05.10. | 3. | L | [[courses:a0m33eoa:en:labs:week_02|LS for binary representation.]] | /*[[https://github.com/honzaMaly/f-evop|f-evop on GitHub]], {{:courses:a0m33eoa:cviceni:sga.zip|SGA in Java}}, {{:courses:a0m33eoa:cviceni:test_function.m|}}, */[[http://www.obitko.com/tutorials/genetic-algorithms/index.php|Marek Obitko: Genetic Algorithms Tutorial]] | | 12.10. | 4. | S | [[courses:a0m33eoa:en:labs:week_03|LS for real-number representation, 1/5 rule.]] | | | 19.10. | 5. | L | [[courses:a0m33eoa:en:labs:week_04|EA for binary/real/permutation representation.]] [[courses:a0m33eoa:en:hw:hw1|HW1 assignment.]] | | | 26.10. | 6. | S | How to present results reasonably. Work on [[courses:a0m33eoa:en:hw:hw1|HW1]] + consultations. **The deadline for HW1 follows on Sunday.** | | | 02.11. | 7. | L | [[courses:a0m33eoa:en:labs:week_06|Implementation of multi-objective EA.]] | | | 09.11. | 8. | S | [[courses:a0m33eoa:en:labs:week_07|Implementation of constraints-related techniques.]] [[courses:a0m33eoa:en:hw:hw2|HW2 assignment]].| | | 16.11. | 9. | L | Introduction to topics for [[courses:a0m33eoa:en:semestral_tasks:start|semestral tasks]]. | | | 23.11. | 10. | S | [[courses:a0m33eoa:en:labs:week_08|Genetic programming - practical example]]. **The deadline for HW2 follows on Sunday.** | /*{{:courses:a0m33eoa:cviceni:sgp.zip|SGP in Java}}*/ | | 30.11. | 11. | L | Work on semestral tasks, consultations. | | | 07.12. | 12. | S | Work on semestral tasks, consultations. | | | 14.12. | 13. | L | Work on semestral tasks, consultations. **The deadline for semestral task follows.** | | | 04.01. | 14. | L | Presentations | | ===== Links ===== * [[courses:a0m33eoa:en:hw:start|Homeworks]] - exercise the methods from lectures on simple examples. * [[courses:a0m33eoa:en:semestral_tasks:start|Semestral tasks]] - solve a more complex, or real-world problem using evolutionary methods.