Welcome to the Rival{Theory} forum discussing the popular online AI class from Stanford. Here we'll be discussing general AI, lessons learned from class, alternate views, and especially topics from the course that are relevant to making games. Please join the discussion!
We have everyone here in our offices doing the advanced course. It will be interesting to see how the Stanford view of AI compares to our own. I tend to argue with the finer points, but think the course content is valuable.
I would love to take the course or follow the course. I will definately keep reading these forums. My current professor did AI for the military for several years and has his own views for pathfinding he likes to share with the class. I guess I will be revisiting my days of A*, hueristics, weighted graphs, and the name Dijkstra(think thats spelled correctly) . Its been a couple years and I remember A* very well. We used a few other algorithms, but I will have to go back to see what they were.
First two sessions were pretty easy and straightforward. HW#1 was not any harder than the quizzes. I think I prefer "show your work" vs multiple choice for the homework, but I imagine that would be ridiculously hard to grade at that scale.
Ouch, last week's classes and HW2 were pretty intense. Can anyone correctly define the meaning of "probability"? And what does it mean for two variables to be "dependent"?