: Partially-observable Markov decision processes provide a very general model for decision-theoretic planning problems, allowing the trade-offs between various courses of actions t...
Execution plans produced by traditional query optimizers for data integration queries may yield poor performance for several reasons. The cost estimates may be inaccurate, the mem...
Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
Traditional query processors generate full, accurate query results, either in batch or in pipelined fashion. We argue that this strict model is too rigid for exploratory queries o...
Abstract— The need for efficient monitoring of spatiotemporal dynamics in large environmental surveillance applications motivates the use of robotic sensors to achieve sufficie...
Amarjeet Singh 0003, Fabio Ramos, Hugh D. Whyte, W...