This chess program changes its strength to give the best match against you. Eventually it learns to beat you specifically through learning alogirthms. Features included transposition tables and a elementary 3-piece endgame tablebase.
In imitative learning, an agent will attempt to match what is observed to their memory. By visualizing the incorrectly matches "scenes", this project will allow algorithm developers to gain a better understanding of what causes their algorithms to fail.