Full text of the second edition of Artificial Intelligence: foundations of computational agents, Cambridge University Press, 2017 is now available.

#### 3.7.5.1 Bidirectional Search

The idea of a bidirectional search is to reduce the search time by searching forward from the start and backward from the goal simultaneously. When the two search frontiers intersect, the algorithm can reconstruct a single path that extends from the start state through the frontier intersection to the goal.

A new problem arises during a bidirectional search, namely ensuring that the two search frontiers actually meet. For example, a depth-first search in both directions is not likely to work well because its small search frontiers are likely to pass each other by. Breadth-first search in both directions would be guaranteed to meet.

A combination of depth-first search in one direction and breadth-first search in the other would guarantee the required intersection of the search frontiers, but the choice of which to apply in which direction may be difficult. The decision depends on the cost of saving the breadth-first frontier and searching it to check when the depth-first method will intersect one of its elements.

There are situations where a bidirectional search can result in
substantial savings. For example, if the forward and backward
branching factors of the search space are both *b*, and the goal is
at depth *k*, then breadth-first search will take time proportional
to *b ^{k}*, whereas a symmetric bidirectional search will take time
proportional to

*2b*. This is an exponential savings in time, even though the time complexity is still exponential. Note that this complexity analysis assumes that finding the intersection of frontiers is free, which may not be a valid assumption for many applications (see Exercise 3.10).

^{k/2}