Over the past few days I’ve been working on my own genetic optimization program. For our senior design project me and 5 other OEs were tasked to design a submarine for a competition. We’re using a Multiple-Objective Genetic Optimization (MOGO) method Dr. Brown has written two papers on it:
I need to check his references at the end of his papers.
What I’ve done…
Topics:
Ideas for research:
(goes into more detail below… read on…)
…At the MIT AI Lab…
http://www.cs.indiana.edu/mit.research.how.to.html
This is an interesting article. Since pretty soon research is going to be ‘my thing’ I think I’m going to follow some of its advice. Namely the advice to read a lot of research that’s going on early, and to organize it and it’s references. So on here I’ll link to papers, and summarize them a bit, like I’ll do in this.
So far this article mentions the important of reading a LOT, taking notes and networking. The reason for reading a lot is to learn from the things people have already done. Something not explicitly mentioned but implied is that the things to read are those that interest you. You should also read with a question in mind (What if…, how can I use this… etc). My notes will be these blog entries. Networking is obvious to me so I already knew that. Another thing about reading, this site stresses the importance of learning other fields. I’ve personally found this to be very helpful, because this is where innovative solutions to problems come from. I’m interested in Artificial Intelligence (which is the MIT department the site is for), submarine design, genetic algorithms, autonomous underwater vehicles, etc and if these can be merged it would spit out something pretty creative.
Anyways, some good stuff in there. Next post will be on what I want to look into for research.
