Moving target search (MTS) or the game of cops and robbers has a broad field of application reach- ing from law enforcement to computer games. Within the recent years research has focused on computing move policies for one or multiple pur- suers (cops). The present work motivates to ex- tend this perspective to both sides, thus developing algorithms for the target (robber). We investigate the game with perfect information for both play- ers and propose two new methods, named TrailMax and Dynamic Abstract Trailmax, to compute move policies for the target. Experiments are conducted by simulating games on 20 maps of the commercial computer game Baldur's Gate and measuring sur- vival time and computational complexity. We test seven algorithms: Cover, Dynamic Abstract Mini- max, minimax, hill climbing with distance heuris- tic, a random beacon algorithm, TrailMax and DA- TrailMax. Analysis shows that our methods outper- form all the other algorithms in quality, achieving up to 98% optimality, while meeting modern com- puter game computation time constraints.