Getting better....

As you can see, the dungeon floor plan generator is getting better.  In fact, it's starting to look more and more like the dungeon floorplans I used to draw up on graph paper when I should have been paying more attention in high school.  :-)

Well, it's now Spring Break (already to the midpoint, actually), so I've had a little extra time to play around with some comp sci topics that I haven't really used much in the past.  Of course I've been having fun with genetic algorithms, but those were easy to learn for me, having a degree in biology.  Not as easy are artificial neural networks.  Haven't much experience with them, so this is new ground for me.  There are many situations, though, that I suspect lend themselves to neural networks more than, say, genetic algorithms.  Regardless, it will be fun to compare and contrast....

Getting there....

Debugging this has been the usual nightmare: any time you nest loops for these, no matter how many times you've done this, you still get mixed up between rows, colums, i, j, x, and y.  Anyway, I just need to clean up the code a bit and make a few adjustments before I can start turning these into environments to explore using the keyboard....

Let's Do Something Fun This Year: Genetic Algorithms!

I have to admit--the new Computer Science lab has made teaching Computer Science so much easier that I rarely feel the need to complain about things.  Sadly, I also blog a lot LESS than I used to.  And that is unfortunate, because our school is quickly becoming a top-notch Computer Science high school.  The more we end up actually doing, however, the less we seem to document it.  That irony stings a bit.


Heck, even using something as innocent as the Apple Remote Desktop has caused me to rely less on Google and the web in general.  Why upload assignments to our class website when I can just click and drag it onto their desktops?  Also, I can improvise stuff on the fly and share it immediately with my students.

Still, there's something to be said for documenting the great things that we do in education.  So what the heck, might as well share one of those things here.  This year Skyline Computer Science students and members of the Skyline Programming Club are working on two major projects that I am very proud of.

The first is PyKata.  PyKata aims to be an open place for teachers and students to practice writing functions in Python.  Of course we were inspired by JavaBat, and we only hope to make PyKata challenging and fun.  This is a way for Skyline's graduating class of programmers to leave behind something for future programmers at Skyline to use for years to come--not to mention anyone else in the world that uses PyKata.

The second is something that occured to me and a few of my senior programmers: working together on a year-long, school-wide case study.  Since there was a lot of interest in a classic example by Melanie Mitchell, we are going to roll up our sleaves and do some old-school science work.  We are going to attempt to repeat her results--to confirm them.  We are then going to add our own style to her study and take it further.  Whereas Mitchell's study dealt with evolving robots efficient at picking up cans--we'd like to give it the Skyline touch and try evolving other types of bots.  Bots that make beautiful art, for instance.  You will see this project develop mostly during the Spring semester, but to get started, check out the project's main page now.

Genetic Algorithms: Summer Fun!

Just thought I'd drop in for a second and post about what I've been up to.

Today I wrote Java code to attempt to reproduce a Genetic Algorithms study that Melanie Mitchell talks about in chapter nine of her excellent book, Complexity: A Guided Tour.

Right now I'm a little brain fried after using both Python and Java to find an easy way to convert a five digit string version of a base three number to a decimal version. Maybe you've done something similar this Summer? :-)

The project in short description is simply a way to use evolution to produce the best algorithm for a near-sighted bot that picks up cans in a large room. It's not the situation that matters as much as it is the method: Genetic Algorithms.

Image is from the Complexity page at Wikipedia.