Terry L. Zimmerman

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We consider the problem of managing schedules in an uncertain, distributed environment. We assume a team of collaborative agents, each responsible for executing a portion of a globally pre-established schedule, but none possessing a global view of either the problem or solution. The goal is to maximize the joint quality obtained from the activities executed(More)
We consider the problem of coordinating a team of agents engaged in executing a set of interdependent , geographically dispersed tasks in an oversubscribed and uncertain environment. In such domains, where there are sequence-dependent setup activities (e.g., travel), we argue that there is inherent leverage to having agents maintain advance schedules. In(More)
We present techniques for incrementally managing schedules in domains where activities accrue quality as a function of the time and resources allocated to them and the goal is to maximize the overall quality of actions executed over time. The scheduling problem of interest is both over-subscribed and dynamic; there is generally more to do than is possible(More)
In this paper, we describe an incremental scheduling framework designed to support joint management of interdependent schedules by multiple executing agents. We assume an uncertain execution environment and a distributed representation of the overall problem and schedule such that no single agent has a complete view. Hence as unexpected execution events(More)
In this paper, we describe an approach to scheduling under uncertainty that achieves scalability through a coupling of deterministic and probabilis-tic reasoning. Our specific focus is a class of over-subscribed scheduling problems where the goal is to maximize the reward earned by a team of agents in a distributed execution environment. There is(More)
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