Evolutionary Algorithms II
The seminar consists of presentations on different selected topics prepared by the students. Ideally, each lesson will contain two presentations, thus, each presentation should be at most 40 minutes including questions and discussion.
You can come up with your topic, or you can choose one from the list bellow. There are two options regarding the content of the presentation: you can either choose an interesting application of evolutionary algorithms, implement it and present the results, or you can "only" study some interesting topic and tell us about it. If the selected topic is also included in the lecture, the presentation should contain something new (interesting application, some new algorithm, etc.). Repeating what Roman said during the lecture does not make sense.
- Choose the topic during the first week of the term and also choose the date for your presentation.
- Send me the details of the presentation (title, short abstract) at least a week before the presentation, so I can put it on the webpage.
- Send me the slides (or other notes, if you do not use slides) after the presentation, so I can put it on the webpage for those who could not come.
- Attend the seminar whenever possible.
Calendar of the seminar
The selected topics and free slots for presentation are in the Google Calendar. If there is no presentation planned for a given day, the seminar is canceled.
List of topics
This list is incomplete, you can choose any other topic, which may be interesting for others and is at least a little connected to natural or artificial evolution, artificial life, or related fields. The links should provide some basic information about the topic, but you should use other sources in the presentation.
Applications of evolutionary algorithms
- Genetic Programming — relatively wide topic, also discussed in the lecture, but there are definitely topics that can be used for presentation (e.g. semantic GP, linear GP, cartesian GP, etc.)
- Graph Drawing — the task is to draw a graph in such a way that no edges cross (or minimize the number of crossing edges)
- Co-evolution — both natural and artificial
- Neuro-evolution — again a wide topic, partially discussed in the lectures, but e.g. EANT can be used for presentation
- Scheduling — wide topic, which is not discussed in the lecture, you can also compare evolutionary and classical techniques
- Evolutionary Art — music and pictures created by evolution (or TORCS race courses)
Theory of evolutionary computation
- Swarm Intelligence — an optimization technique inspired by the behavior of swarms
- Ant Colony Optimization — optimization algorithm inspired by ants
- Harmony search — inspired by the improvisation in music
- Artificial Immune Systems — inspired by the Immune System
- Estimation of Distribution Algorithms — algorithms, which generate new individuals from an estimated probability distribution
- Evolutionary Theories — including old ones, Lamarckism, Baldwinism, Darwinism, but other types of evolution can also be interesting — socio=cultural, technological.
- Artificial Life — both software- and hardware-based