Rodents are able to navigate within dynamic environments by constantly adapting to their surroundings. Hippocampal place-cells encode the animals current location and fire in sequences during path planning events. Place-cells receive excitatory inputs from grid-cells whose metric system constitute a powerful mechanism for vector based navigation for both known and unexplored locations. However, neither the purpose or the behavioral consequences of such mechanism are fully understood. During early exploration of a maze with multiple discrimination points, rodents typically manifest a conflict-like behavior consisting of alternating head movements from one arm of the maze to the other be- fore making a choice, a behavior which is called vicarious trial and error (VTE). Here, we suggest that VTE is modulated by the learning process between spatial- and reward-tuned neuronal populations. We present a hippocampal model of place- and grid-cells for both space representation and mental travel that we used to control a robot solving a foraging task. We show that place-cells are able to represent the agents current location, whereas grid-cells encode the robots movement in space and project their activity over unexplored paths. Our results suggest a tight interaction between spatial and reward related neuronal activity in defining VTE behavior.