[jjn2009]

Its computationally difficult to calculate every possible move a character might do in the occluded region. This requires a long attention span and running simulations of possible opponent actions based on previous 'frames'. Alpha go solved some of this by reducing the amount of space searching and instead search the likely set of possible choices by the opponent but each evaluation is for a single frame. If for some reason a piece on a go board could disappear and reappear then during that time it was gone its impact on decision making would be either nil or skew heavily towards nil compared to the rest of the opponents pieces depending on how many frames in the past are used.