The horizon effect (or horizon problem) is a problem in artificial intelligence.

When evaluating a large game tree (for instance using minimax or alpha-beta pruning), search depth is often limited for feasibility reasons. Sometimes evaluating a partial tree may give a misleading result. When a significant change exists just over the "horizon", slightly beyond the depth of search, one falls victim to the horizon effect.

(Acknowledgments to Wikipedia)