This week I spent my time working on the find_best_shot algorithm for the physics simulation portion of our project. Currently, my approach is good and finds the 9-ball shot that: a) hits the lowest numbered ball on the table, b) does not result in a scratch, c) pots 1+ balls, d) sets up the cue ball to be closest to the lowest numbered ball on the table, and e) occasionally pots the 9 ball if possible.
However, I am still using more of a brute-force approach than a greedy one. I am thinking of ways to use some Simulated Annealing to find the optimal shot we can take. This will require tweaking parameters that determine the “score” of a shot — this includes balls potted, where the cue ball ends up, etc. I will be spending my time this upcoming week implementing my algorithm and optimizing it to complete in under four seconds as specified by our use-case requirements.
I am still on schedule and, again, hope to be done with the best shot algorithm + display mapping before carnival so that we can test MVP.
