Spatial Navigation in Virtual World

Absract One of the most challenging and complex tasks when working with virtual worlds is the navigation process. This chapter presents the possibilities of using neural networks as a tool for studying spatial navigation within virtual worlds. How it learns to predict the next step for a given trajectory, acquiring basic spatial knowledge in terms of landmarks and configuration of spatial layout. In addition, how it builds a spatial representation of the virtual world, rather like a cognitive map. The benefits of this approach and the possibility of extending the methodology to the study of navigation in Human Computer Interaction (HCI) and other applications are described in brief. The study of computation models of navigation and the potential of using cognitive maps in the modeling of navigational processes are described. Non-visual spatial learning model is presented for the spatial learning through virtual world exploration. Different types of locomotion in virtual world with their constraints and benefits are discussed. Intended readers of the chapter would be the mobility trainer, architect, city planner, cartographer, psychologist, and game developer