s, minus costs. This is optimizing for <em>cumulative regret</em>: minimizing the sum of each instance of regret corresponding to the difference between the best possible payout and actual payout for that play. PUCT, UCT and UCB concern themselves with cumulative regret, and this can work quite well. However, a better optimization target when thinking about tree search in chess is <em>simple regret</em>, wherein after a search period, a single instance of regret is incurred based on a single, final play.</p