Abstract. Believable spatial behaviour is important for intelligent virtual agents acting in human-like environments, such as buildings or cities. Existing models of spatial cognition and memory for these agents are predominantly aimed at issues of navigation and learning of topology of the environment. The issue of representing information about possible objects ’ locations in a familiar environment, information that can evolve over long periods, has not been sufficiently studied. Here, we present a novel representation for “what-where” information: memory for locations of objects. On a simplified model of a virtual character living in a virtual house, we investigate how this representation is formed and how it evolves based on how objects...