Present-day cognitive science research is marked by a variety of formal modeling approaches, characterized by different emphases, methodologies, and strengths. These range from highly detailed neural models of particular brain areas and functions to cognitive architectures aiming to capture general features of human information processing, and from formal mathematical treatments of cognitive phenomena to algorithms targeting optimal solutions in artificial intelligence.

These modeling approaches have all been utilized in research efforts in the area of spatial information processing. Neural models have benefited from the enormous growth in neuroimaging research, which has produced extensive neuropsychological and neurophysiological evidence enumerating critical brain areas in spatial processing, and identifying important characteristics of their structure, interconnectivity, and functional characteristics. Meanwhile, exponential increases in computer processing power have enabled robotics research on navigation and cognitive mapping, with mathematical models and algorithms forming the foundation for spatially aware autonomous agents. Increased computing power has also led to compellingly realistic virtual environments, creating a foundation for expanded roles for simulation beyond computer gaming and leading to greater demand for agents in simulations with greater cognitive fidelity and flexibility. Cognitive architectures provide a means of integrating spatial information processing with a broader set of cognitive capabilities to support such potential applications.

Tremendous progress has been achieved on all of these fronts. This workshop is motivated by the potential for even greater progress through more explicit communication and interaction to integrate the strengths of different modeling approaches. An ultimate goal of research in this area is to arrive at an understanding of human spatial competence that is cognitively and neurally plausible, which will allow for detailed, quantitative accounts of empirical and neural phenomena while providing extensive functionality. This workshop will bring together leading researchers to consider current challenges, and to identify a path forward toward achieving this goal.