Spatial search problems abound in the real world, from locating hidden nuclear or chemical sources to finding skiers after an avalanche. We exemplify the formalism and solution for spatial searches involving two agents that may or may not chose to share information during a search. We show that, for certain classes of tasks, sharing information between multiple searchers makes cooperative searching advantageous. We give examples in which agents are able to realize synergy by aggregating information and moving based on local judgments about maximal information gathering expectations. We explore one- and two-dimensional simplified situations analytically and numerically to provide a framework for analyzing more complex problems. These general considerations provide a guide for designing optimal algorithms for real-world search problems.