A cloud robot meta-reasoner driven by semantic attention maps and unsupervised Bayesian belief updates outperforms generic and hand-coded meta-reasoners in unexpected radio and edge-switching scenarios.
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Meta-reasoning Using Attention Maps and Its Applications in Cloud Robotics
A cloud robot meta-reasoner driven by semantic attention maps and unsupervised Bayesian belief updates outperforms generic and hand-coded meta-reasoners in unexpected radio and edge-switching scenarios.