R1-[ImageSpace] - Details

Mental Representations of Spatial Environments


Mental reasoning about spatial environments is often based on spatio-analogical or quasipictorial representation structures. As human working memory for spatio-analogical knowledge processing is severely restricted in capacity, mental processes dynamically construct and explore task-sensitive representations to obtain a desired piece of spatial information. Although models of partial aspects of spatial mental image processing and of reasoning with mental models already exist, there is no computational architecture yet that describes spatial mental knowledge processing as a whole.

Of special interest in this respect are the dynamic inter-operation between the mental components involved and the interaction between internal and external diagrammatic representations.
The goal of the project is to model the construction and inspection of mental representations of spatial environments and to explore these models computationally. The project aims at designing and implementing a processing architecture that serves as a computational description of the corresponding mental processes. We analyze the dynamic operation of the architecture and investigate the feedback characteristics between the different processing instances involved. This analysis of the model leads to design steps and extensions of the model. The resulting models will be applied in a prototypical spatial task assistance system that complements internal representations by external representations interactively to compensate mental processing restrictions.

The project is carried out from an interdisciplinary perspective. We analyze empirical findings with respect to the characteristics of the knowledge involved in mental image construction. We design a conceptual model of human reasoning about spatial environments that is based on these empirical findings. This conceptual model serves as the basis for the specification and design of the computational model proper.

Also the interactions between internal representations of the environment and external representations that mimic the characteristics of mental representation structures (e.g., schematic maps) require further research. Based on the model developed the emphasis will be set on the interaction between internal and external representations. This will be done from two perspectives. First, external representations will be integrated into the model as external extensions of the modeled internal spatio-analogical representations. Second, the model extended in this way will be investigated with respect to the prototypical application. The challenging question is, how internal and external spatial representations can be integrated into a common framework to overcome reasoning restrictions due to capacity limitations.