Iterative deepening! The bot now searches depths in an ascending order instead of descending. This is only possible thanks to my transposition tables but means that I can give the bot a time limit. Once the time limit is reached it just return the best move of the highest depth its fully searched. This means that I can search to different depths in different positions whilst making sure I always play within the time limit. This is good as it means I can have a high depth during the opening and endgame whilst having a medium depth during mid game instead of having a medium depth everywhere to ensure moves at midgame don’t take too long. Midgame usually has a lower depth due to the high number or possible moves that can be played. I can also easily change the time limit with just a single variable. This means I can get my bot to play faster but also worse or take longer but play better. I added incremental evaluation. This means that for each move, instead of looping through all 12 bitboards and recalculating the evaluation score from scratch I instead update it from the current evaluation score. So when I move a piece I subtract its old it’s material value and then add the material value if it still exists. The same happens for the position bonuses. This takes my time complexity from O(n) to O(1) which is a massive upgrade. These changes lets my depth in early game and endgame almost always stay at 7 whilst during midgame hover between depth 6 and depth 7. Currently I determine if I am in endgame if both queens are gone and the total amount of pieces is below 16 however I feel that this isn’t a good measure and I should improve this. Next I will try to improve efficiency by improving my move ordering so that the alpha beta pruning is more efficient.