Searched for: subject%3A%22State%255C+representation%255C+learning%22
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meo, cristian (author)
Active inference, a theoretical construct inspired by brain processing, is a promising approach to control artificial agents. Here we present a novel multimodal active inference torque controller for industrial arms that improves the adaptive characteristics of previous active inference approaches but also enables multimodal integration with any...
master thesis 2021
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Duan, Wuyang (author)
Representation learning is a central topic in the field of deep learning. It aims at extracting useful state representations directly from raw data. In deep learning, state representations are usually used for classification or inferences. For example, image embedding that provides similarity metrics can be used for face recognition. Recent...
master thesis 2017
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Munk, J. (author)
In control, the objective is to find a mapping from states to actions that steer a system to a desired reference. A controller can be designed by an engineer, typically using some model of the system or it can be learned by an algorithm. Reinforcement Learning (RL) is one such algorithm. In RL, the controller is an agent that interacts with the...
master thesis 2016