In this work we address a game theoretic variant of the shortest path problem, in which two decision makers (agents/players) move together along the edges of a graph from a given starting vertex to a given destination. The two players take turns in deciding in each vertex which edge to traverse next. The decider in each vertex also has to pay the cost of the chosen edge. We want to determine the optimal path where each player minimizes its costs taking into account that also the other player acts in a selfish and rational way. Such a solution can be determined by backward induction in the game tree of the associated finite game in extensive form. We show that finding such an optimal path is PSPACE-complete even for bipartite graphs both for the directed and the undirected version of the game. On the other hand, we can give polynomial time algorithms for directed acyclic graphs and for cactus graphs even in the undirected case. The latter is based on a decomposition of the graph into components and their resolution by a number of fairly involved dynamic programming arrays.