A different take on the best-first game tree pruning algorithms
  The alpha-beta pruning algorithms have been popular in game tree searching
ever since they were discovered. Numerous enhancements are proposed in
literature and it is often overwhelming as to which would be the best for
implementation. A certain enhancement can take far too long to fine tune its
hyper parameters or to decide whether it is going to not make much of a
difference due to the memory limitations. On the other hand are the best first
pruning techniques, mostly the counterparts of the infamous SSS* algorithm, the
algorithm which proved out to be disruptive at the time of its discovery but
gradually became outcast as being too memory intensive and having a higher time
complexity. Later research doesn't see the best first approaches to be
completely different from the depth first based enhancements but both seem to
be transitionary in the sense that a best first approach could be looked as a
depth first approach with a certain set of enhancements and with the growing
power of the computers, SSS* didn't seem to be as taxing on the memory either.
Even so, there seems to be quite difficulty in understanding the nature of the
SSS* algorithm, why it does what it does and it being termed as being too
complex to fathom, visualize and understand on an intellectual level. This
article tries to bridge this gap and provide some experimental results
comparing the two with the most promising advances.
