In this blog, I will be reviewing on how I thought the Natural Computing course that I had taken at Goldsmiths University was. I will be reflecting on the topics it covered, how they were covered and what I had learned over the duration of the course.
Here are the following topics, concepts and techniques that were taught over the 10 week course:
- No Free Lunch
- Dispersive Flies Optimisation
- Stochastic Diffusion Search
- Understanding the fitness function
- Genetic Algorithms
- Ant Colony Optimisation
How they were covered
I feel that they were covered very well and in a logical order so that, as a student jumping into a brand new and scary field, it was easy to understand. Without learning about “No Free Lunch”, I would have not understood that one technique is not the solution to all problems.
The way that the techniques were taught were very good as well, and each of them covered different bases. I was able to interact with the code and write programs that were able to use the techniques, which furthered my understanding more.
I feel that I cannot pinpoint the single best thing that I have learnt over the course as there were a lot of topics that I enjoyed. If I had to choose a mix of the techniques that I enjoyed the most, those would be SDS and genetic algorithms. Both of these, I feel, are easy to implement into a problem and can open your mind to thinking with nature in mind.
The End Part
If you, as the reader, are interested in some of the topics that I have discussed; please read the rest of my blog posts where I talk about them in a lot more detail. Link
The lecturer of the course does a lot in this field and much of his work is very interesting. Although this video was 2 years ago, it is still pretty cool. A swarm drawing a picture:
So check out the rest of his work on: