A Deep Incremental Boltzmann Machine for Modeling Context in Robots

Abstract

Context is an essential capability for robots that are to be as adaptive as possible in challenging environments. Although there are many context modeling efforts, they assume a fixed structure and number of contexts. In this paper, we propose an incremental deep model that extends Restricted Boltzmann Machines. Our model gets one scene at a time, and… (More)

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Cite this paper

@article{Dogan2017ADI, title={A Deep Incremental Boltzmann Machine for Modeling Context in Robots}, author={Fethiye Irmak Dogan and Sinan Kalkan}, journal={CoRR}, year={2017}, volume={abs/1710.04975} }