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We consider the problem of on-line continual planning, in whichadditional goals may arrive while plans for previous goals are stillexecuting and plan quality depends on how quickly goals are achieved.This is a challenging problem even in domains with deterministicactions. One common and straightforward approach is reactive planning,in which plans are synthesized when a new goal arrives. In this paper,we adapt the technique of hindsight optimization from on-line schedulingand probabilistic planning to create an anticipatory on-line planningalgorithm. Using an estimate of the goal arrival distribution, wesample possible futures and use a deterministic planner to estimate thevalue of taking possible actions at each time step. Results in twobenchmark domains based on unmanned aerial vehicle planning andmanufacturing suggest that an anticipatory approach yields a superiorplanner that is sensitive not only to which action should be executed,but when.