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Interaction is More Beneficial in Complex Reinforcement Learning Problems than in Simple Ones

, , , and . Interdisziplinärer Workshop Kognitive Systeme: Mensch, Teams, Systeme und Automaten, page 142-150. (March 2015)

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Robot Docking Based on Omnidirectional Vision and Reinforcement Learning., , and . SGAI Conf., page 23-36. Springer, (2005)KT-Speech-Crawler: Automatic Dataset Construction for Speech Recognition from YouTube Videos., , , and . CoRR, (2019)What can computational models learn from human selective attention? A review from an audiovisual crossmodal perspective., , , , , , , , and . CoRR, (2019)Interaction is More Beneficial in Complex Reinforcement Learning Problems than in Simple Ones, , , and . Interdisziplinärer Workshop Kognitive Systeme: Mensch, Teams, Systeme und Automaten, page 142-150. (March 2015)Virtual or Physical? Social Robots Teaching a Fictional Language Through a Role-Playing Game Inspired by Game of Thrones., , , , , , , , , and 10 other author(s). ICSR, volume 11876 of Lecture Notes in Computer Science, page 358-367. Springer, (2019)Predictive Auxiliary Variational Autoencoder for Representation Learning of Global Speech Characteristics., , , and . INTERSPEECH, page 934-938. ISCA, (2019)LipSound: Neural Mel-Spectrogram Reconstruction for Lip Reading., , and . INTERSPEECH, page 2768-2772. ISCA, (2019)How do we approach intrinsic motivation computationally.. Frontiers Neurorobotics, (2008)Structured Models from Structured Data: Emergence of Modular Information Processing within One Sheet of Neurons., and . IJCNN (4), page 608-613. IEEE Computer Society, (2000)0-7695-0619-4.The Impact of Personalization on Human-Robot Interaction in Learning Scenarios, , , , , , , , , and 8 other author(s). International Conference on Human-Agent Interaction (HAI), 5th, page 171--180. Bielefeld, Germany, ACM, (October 2017)