Jim Carnicelli's AI Blog

[ Audio Version ] I've made quite a bit of progress along the way of this project. It would be tedious to document the full progression since the start. Still, I suppose I should get in the habit of documenting progress from time to time. Since my previous posting, when I wrote an opening summary of the Roamer project, I've made some significant progress. Most importantly, I noticed a memory leak that was occurring because of the poor way I was using the graphics features of the .NET framework. I'm a bit disappointed that it doesn't seem to deal well with cleaning up after itself. With a little effort, I eliminated that memory leak nearly completely. It's hard to tell, though, because, as the .NET documentation indicates, garbage collection doesn't happen immediately as objects are removed from use. One exciting change is that now I can define a world using an XML file. Previously, I had to hard-code the initializations of each demonstration. It's no

[ Audio Version ] I keep trying to figure out how to get started with this blog. I'm in the process of a new research project, but I don't really have a lot of time now to describe it in detail. Yet I think it'll be worthwhile to give updates as it progresses. So I guess the best compromise is to at least summarize my current project. For various reasons, I've called it "Roamer". One of my first design goals was to do what I've wanted to for many years: to create a rich "physical" environment that can be used for AI and AL research. I've basically succeeded in that already. The environment allows for one or more "planets", like Petri dishes with their own different experiments. Each planet is a 2-dimensional, rectangular region populated by various barriers, force fields and, most importantly, particles. All "critters" are composed of particles, basically circles with distinct masses, radii, colors, and so on tha

[ Audio Version ] This is my first entry into this blog. The subject matter generally is Artificial Intelligence. I have been engaged in AI research in one way or another since around 1990, when I first read the Time-Life book "Alternative Computers", part of their "Understanding Computers" series, a colorful if brief look from a layman's perspective at a variety of technologies that even today get the statuses of cutting edge or bold speculation. As I recall, it touched on neural networks, nanocomputers, optical computing, and so on. Given my intense interest at the time in robotics and digital processors, what most caught my eye was a section on artificial intelligence. At that time, I had followed an odd path that led me from studying simple electronics to digital logic and all the way up to microprocessor architecture. What I was finally realizing around this time was that in order to understand how digital computers worked, I was going to have to learn how