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Although Deep Neural Networks reached remarkable performance on severalbenchmarks and even gained scientific publicity, they are not able to addressthe concept of cognition as a whole. In this paper, we argue that thosearchitectures are potentially interesting for cognitive robots regarding theirperceptual representation power for audio and vision data. Then, we identifycrucial settings for cognitive robotics where deep neural networks have as yetonly contributed little compared to the challenges in cognitive robotics.Finally, we argue that the rather unexplored area of Reservoir Computingqualifies to be an integral part of sequential learning in this context.

Potentials and Limitations of Deep Neural Networks for Cognitive Robots