We investigate the problem of keeping the plans of mul- tiple agents synchronized during execution. We assume that agents only have a partial view of the overall plan. They know the tasks they must perform, and know the tasks of other agents with whom they have direct depen- dencies. Initially, agents are given a schedule of tasks to perform together with a collection of contingency plans that they can engage during execution in case execu- tion deviates from the plan. During execution, agents monitor the status of their tasks, adjusting their local schedules as necessary and informing dependent agents about the changes. When agents determine that their schedule is broken or that a contingency schedule may be better, they engage in coordinating plan changes with other agents. We present a "dynamic partial central- ization" approach to coordination. When a unit detects a problem (task delay, inability to perform a task), it will dynamically form a cluster of the critically affected agents (a subset of all potentially affected agents). The cluster will elect a leader, who will retrieve all task and contingency plan information from the cluster members and compute a solution depending on the situation.