ANONYMOUS wrote: As has been addressed before, your agent should not assume it remains between games. To be considered to consistently outperform another agent, then your agent, when dropped into an identical random situation as the other agent, should have a higher expected win rate. You are welcome to have your agent learn more if it is put through multiple rounds to improve its play, but there is no guarantee given in the specification that it will be given time to learn before being assessed. So in effect, this is asking: Why are you making things harder for yourself by making your agent learn from zero while being assessed? Why are you throwing out all the learning it has already done? It is impossible to win every single game even with expert play, so that is not the requirement. But your agent should be effective in any situation it is put in, and that includes its first game.