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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 6 of 6 1 Grounding Hindsight Instructions in Multi-Goal Reinforcement Learning for Robotics ... Röder, Frank; Eppe, Manfred; Wermter, Stefan. - : arXiv, 2022 BASE Show details 2 Towards a self-organizing pre-symbolic neural model representing sensorimotor primitives ... Zhong, Junpei; Cangelosi, Angelo; Wermter, Stefan. - : arXiv, 2020 BASE Show details 3 Incorporating End-to-End Speech Recognition Models for Sentiment Analysis ... Lakomkin, Egor; Zamani, Mohammad Ali; Weber, Cornelius. - : arXiv, 2019 BASE Show details 4 Towards Dialogue-based Navigation with Multivariate Adaptation driven by Intention and Politeness for Social Robots ... Bothe, Chandrakant; Garcia, Fernando; Maya, Arturo Cruz. - : arXiv, 2018 BASE Show details 5 GradAscent at EmoInt-2017: Character- and Word-Level Recurrent Neural Network Models for Tweet Emotion Intensity Detection ... Lakomkin, Egor; Bothe, Chandrakant; Wermter, Stefan. - : arXiv, 2018 BASE Show details 6 Interactive Natural Language Acquisition in a Multi-modal Recurrent Neural Architecture ... Heinrich, Stefan; Wermter, Stefan. - : arXiv, 2017 Abstract: For the complex human brain that enables us to communicate in natural language, we gathered good understandings of principles underlying language acquisition and processing, knowledge about socio-cultural conditions, and insights about activity patterns in the brain. However, we were not yet able to understand the behavioural and mechanistic characteristics for natural language and how mechanisms in the brain allow to acquire and process language. In bridging the insights from behavioural psychology and neuroscience, the goal of this paper is to contribute a computational understanding of appropriate characteristics that favour language acquisition. Accordingly, we provide concepts and refinements in cognitive modelling regarding principles and mechanisms in the brain and propose a neurocognitively plausible model for embodied language acquisition from real world interaction of a humanoid robot with its environment. In particular, the architecture consists of a continuous time recurrent neural network, where ... : Received 25 June 2016; Accepted 1 February 2017 ... Keyword: Computation and Language cs.CL; FOS Biological sciences; FOS Computer and information sciences; Neurons and Cognition q-bio.NC URL: https://dx.doi.org/10.48550/arxiv.1703.08513 https://arxiv.org/abs/1703.08513 BASE Hide details

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