In order to interact with a target object, an agent must determine that it is not within a suitable distance and must therefore locomote to a task-dependent position and orientation prior to the initiation of the reach and grasp. Such a decision is readily made by embedding it in a PaT-Net representing potential actions that enable the specified action. Moreover, the locomotion process itself uses the two level architecture: at the lowest level the agent or avatar gets a goal and an explicit list of objects to be avoided; the other level encapsulates locomotion states and decisions about transitions. For example, the agent could be walking, hiding, searching, or chasing. If walking, then transitions can be based on evaluating the best position of the foot relative to the goal and avoidances. If hiding, then assessments about line of sight between virtual humans are computed. If searching, then a pattern for exhaustively checking the local geometry is invoked. Finally, if chasing, then the goal is the target object; but if the target goes out of sight, the last observed position is used as an interim goal. These sensing actions and resulting decisions are captured in the LocoNet .