Most major roadways (at least in my moderately sized city of around 4 million) have traffic cameras all up and down them that are freely accessible. I'm guessing this would be a valid strategy - run image analysis on all of the traffic cams you can get your hands on for red balloons.

Wouldn't surprise me if this is what the purpose of the contest is - to get someone to develop this software for them.

This sounds like a great approach. If you read my post below, many of the teams start at what you have called the Conscious Individual. If they finish that with enough time, I've seen them move on to the Squad and Command levels also. The main difference though is that since our game state has traditionally been pretty simple, there hasn't been a need to compose a simpler model of the state for the upper levels.

The multi-tiered AI approach does seem very useful and intuitive though.

The ACM Chapter that I preside over at Missouri S&T (Formerly the University of Missouri - Rolla) has been writing simple RTS games with AI APIs for the last two semesters. We're currently working on a third game to add to our repertoire. We host a tournament at the end of each semester and invite anyone that will come - the main site is at http://acm.mst.edu/~mstai. The API is easy enough to get a handle on that a C++ novice could pick it up and do something with it within a few hours. Competitors are given 24 hours to write their AI, then we pit them against each other. Generally speaking, for the RTS style games we have written, AIs that act on an individual unit level only perform the best (both in execution time and scoring). This is probably due to the 24 hour time limit imposed, but it does show that even simple/greedy algorithms can perform well in game AI situations. I believe the winning team of our first tournament had an algorithm that went like this: for each unit: doBestActionForUnit(unit)