A singleton model hold chess board history table information.
History heuristics are in some way an extension of killer moves.
With killer moves, the problem is that we forget them again immediately.
You can think of killer moves as some kind of short-term memory,
while history heuristics is long-term memory.
In history heuristics we keep track of all good moves.
For a game like chess or checkers, we take a double-indexed counter array,
history[][], which we index with the from and to squares of the move.
Every time we find a move from a-to-b to be good, we increment the value of history[a][b].
When we generate the movelist,
we can then order it according to the values of the history array.
You might want to experiment with the history heuristic too,
e.g. you could decide only to increment the counter for moves which caused a fail-high
(after all, in all other nodes you will have to search all moves anyway,
so it doesn't matter as much in which order you search them).
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