Adjustable autonomy refers to agents' dynamically varying their own autonomy, transferring decision making control to other entities (typically human users) in key situations. Determining whether and when such transfer of control must occur is arguably the fundamental research question in adjustable autonomy. Practical systems have made significant in-roads in answering this question and in providing high-level guidelines for transfer of control decisions. For instance,  report that Markov decision processes were successfully used in transfer of control decisions in a real-world multiagent system, but that use of C4.5 led to failures. Yet, an underlying theory of transfer of control, that would explain such successes or failures is missing. To take a step in building this theory, we introduce the notion of a transfer-of-control strategy, which potentially involves several transfer of control actions. A mathematical model based on this notion allows both analysis of previously reported implementations and guidance for the design of new implementations. The practical benefits of this model are illustrated in a dramatic simplification of an existing adjustable autonomy system.