Teams to exploit spatial locality among agents
نویسندگان
چکیده
In many situations, task allocation is highly dependent on the spatial locality of the agents and the tasks. In this paper we explore task allocation in complex spatial environments, where the cost of completing a task can vary over time. This work focuses on a subset of cost functions for tasks that grow over time and presents the real-time Latest Finishing First (RTLFF) algorithm, which strikes a balance between the optimal zero travel time solution and minimizing the amount of time agents spend transferring to tasks in different locations. We also present how spatial knowledge can be used to infer missing knowledge in partially observable spaces.
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تاریخ انتشار 2013