Until recently, techniques for AI plan generation relied on highly restrictive assumptions that were almost always violated in real-world environments consequently, robot designers adopted reactive a r c hitectures and avoided AI planning techniques. Some recent research e fforts have focused on obviating such assumptions by developing techniques that enable the generation and execution of plans in dynamic, uncertain environments. In this paper, we d i scuss one such t e c hnique,

more »

... d m o nitoring, originally introduced by V eloso, Pollack, and Cox 9], and describe our use of it in a simple mobile robot environment. We review the original approach, describe how i t c a n b e adapted for a causal-link planner, and provide experimental results demonstrating that it can lead to improved plans without consuming excessive o verhead. We also describe our use of rationale-based monitoring in a mobile robot o ce-assistant project currently in progress.