[EN] Basic Information and Requirements

The goal of the seminar is to experiment with the evolutionary algorithms and find out how they behave while solving simple tasks. To this end, we will use a simple Python library. Your goal will be to augment/create an operator to make the algorithm perform better. You will not need a deep understanding of Java/Python - only the basics which are similar in most modern languages are required.

Credit requirements

There will be 12 lessons during the semester. In 11 of these lessons, there will be an assignment and it will be possible to get 5 points for each assignment, i.e. 55 points for the whole term. Additionally, many of the assignments will contain bonus questions (e.g. for solving an extended version of the assignments, or for having a good solution compared to the rest of the class).

You will submit the solutions to the assignments after we finish a group of assignments on a single topic. For example, there will be three lessons on continuous optimization, so you will submit all continuous optimization assignments after the third lesson. The deadline for the submission will be 2 weeks after the last lesson in each group. Instead of submitting to Moodle, you can also show me your solution in the lesson. In order to get the full amount of points, you need to submit the solution before the deadline. If you submit the solution less than two weeks after the deadline, you can still get half the points. Some of the bonus assignments will have shorter deadlines (typically one week).

In order to get the credit for the seminar, you need to have at least 36 points.

Each submitted solution should be accompanied by a short textual description of what you did and a convergence graph that shows the performance of the algorithm. More detailed requirements for the solutions and a tutorial on the creation of plots is on a special page.