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Wireless sensor networks are poised to revolutionize our abilities in sensing and controlling our environment. Power conservation is a primary research concern for these networks. Often, the single most important savings can be obtained by switching off the wireless receiver when not needed. In this paper, we describe an algorithm which allows the nodes to learn the behavior of each other by only observing the transmission behaviors, and from this derive the schedule without external help. Our approach is robust to statistical variations in the nodal transmission periods. We draw important conclusions on the effect of quasi-periodicity on the scalability of the solution. We provide results of numerical simulations that show the effectiveness of our approach.