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The alpha-beta pruning algorithms have been popular in game tree searchingever since they were discovered. Numerous enhancements are proposed inliterature and it is often overwhelming as to which would be the best forimplementation. A certain enhancement can take far too long to fine tune itshyper parameters or to decide whether it is going to not make much of adifference due to the memory limitations. On the other hand are the best firstpruning techniques, mostly the counterparts of the infamous SSS* algorithm, thealgorithm which proved out to be disruptive at the time of its discovery butgradually became outcast as being too memory intensive and having a higher timecomplexity. Later research doesn't see the best first approaches to becompletely different from the depth first based enhancements but both seem tobe transitionary in the sense that a best first approach could be looked as adepth first approach with a certain set of enhancements and with the growingpower 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 theSSS* algorithm, why it does what it does and it being termed as being toocomplex to fathom, visualize and understand on an intellectual level. Thisarticle tries to bridge this gap and provide some experimental resultscomparing the two with the most promising advances.

A different take on the best-first game tree pruning algorithms