We study the problem of a decision maker (DM) trying to reach a party whose location is uncertain. She has a prior probability distribution over the potential locations of the party, her search path is constrained, and she has the objective of reaching the party as quickly as possible. We refer to the problem as the Party Search Problem (PSP). We first show how the PSP can be formulated as a partially observable Markov decision process (POMDP). Next, we show that certain features of the problem make it easily solvable by conventional dynamic programming methods. Finally, we present data from a laboratory experiment in which financially motivated subjects played the PSP. Our results show that subjects display significant "navigational waste." That is, they take travel paths that significantly lengthen their search time, compared to the optimal travel plans. These inefficiencies arise from several behavioral biases. For instance, they tend make "u-turns" too soon during their search. This work brings together ideas from operations research, computer science, and experimental psychology. |