After commenter Hans told me that my Sínat game wasn't playing up to par with him, I decided to see whether I could code a better strategy into the game. I figured it shouldn't be hard to make an improvement. Afterall, the only thing the computer is programmed to do is to find a list of available moves and then pick a move randomly from that list. How could any strategy be worse than that?
A few days ago, I coded a new strategy on my computer to test out. Basically I told my program to evaluate each move and favour those moves which yielded greater protection of one's own pieces at the greatest expense of its opponent's protection. Seems right, yes? Apparently not. After I played the game, I still came out on top without much fuss and that got me a little curious.
So I decided that I would seperate my random algorithm from this new algorithm and have them battle it out. I called the "random" strategy Lateesha, for kicks, while I baptized the other "protection" strategy Shanequa. With Lateesha in red and Shanequa in blue I unleashed the two algorithms against each other for 20 turns to see what the statistical outcome would be.
The results were surprising. Our ol' lady of the block Lateesha won 55% of the time (11 out of 20 moves) over the new kid Shanequa!! What?? Yes, apparently randomness is better than being protective! It appears that this game does not reward overcautiousness because by being too focussed on one's own protection, one's pieces will be slower to get to the end of the board while one's opponent's pieces may pass one by. As a result, I've so far changed nothing in the A.I. programming.
Now I have to think up a better strategy. Back to the drawing board.