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This paper develops a Bayesian probability formula to infer the presence of targets given multiple, noisy detection reports. This problem is characterized by having only positive reports, because the absence of a target is rarely transmitted to the fusion center. Further characteristics of this problem are spatial uncertainty in detection locations and high false alarm rates. In this paper, we develop...
A probabilistic framework for interactive learning in continuous and multimodal perceptual spaces is proposed. In this framework, the agent learns the task along with adaptive partitioning of its multimodal perceptual space. The learning process is formulated in a Bayesian reinforcement learning setting to facilitate the adaptive partitioning. The partitioning is gradually and softly done using Gaussian...
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