State space search is a process used in the field of computer science, including artificial intelligence (AI), in which successive configurations or states of an instance are considered, with the intention of finding a goal state with the desired property.
State space search often differs from traditional computer science search methods because the state space is implicit: the typical state space graph is much too large to generate and store in memory.
, in which: According to Poole and Mackworth, the following are uninformed state-space search methods, meaning that they do not have any prior information about the goal's location.
[1] These methods take the goal's location in the form of a heuristic function.
[2] Poole and Mackworth cite the following examples as informed search algorithms: