This article describes techniques that have been developed for spatial learning in dynamic environments and a mobile robot system, ELDEN, that integrates these techniques for exploration and navigation in dynamic environments. In this research, we introduce the concept of adaptive place networks, incrementally-constructed spatial representations that incorporate variable-confidence links to model uncertainty about topological adjacency. These networks guide the robot's navigation while constantly adapting to any topological changes that are encountered. ELDEN integrates these networks with a reactive controller that is robust to transient changes in the environment and a relocalization system that uses evidence grids to recalibrate dead reckoning. Footnotes 1 Manuscript received . . . 2 Department of Computer Engineering and Science, Case Western Reserve University, Cleveland, OH, 44106, USA (email: firstname.lastname@example.org, URL: http://yuggoth.ces.cwru.edu/yamauchi/index.ht..