What is the expected performance gain of adding Transposition Tables and then MTD(f) to pure alpha beta pruning for chess?
In my pure alpha beta pruning I use the following move ordering:
- principal variation (from previous iterative deepening iteration)
- best move from transposition table (if there is any)
- captures: highest captured then lowest capturing
- killer moves
- history heuristics
With above setup I get following average results for depth 9:
- pure alpha beta: X nodes visited
- alpha beta+TT: 0.5*X nodes visited
- MTDF(f): 0.25*X nodes visited
I expected better results and I wanted to make sure if that's as good as it can get or if there is something wrong with my implementation?
I search with accuracy of 0.1 pawn.
