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    • Mohan, Vishwanathan (7)
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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 – 7 of 7 1 Humanoid infers Archimedes' principle: understanding physical relations and object affordances through cumulative learning experiences Bhat, Ajaz Ahmad; Mohan, Vishwanathan; Sandini, Giulio. - : The Royal Society, 2016 BASE Show details 2 Embodied language learning and cognitive bootstrapping: methods and design principles Zeschel, Arne; Morse, Anthony; Rohlfing, Katharina. - : SAGE, 2016 BASE Show details 3 Embodied Language Learning and Cognitive Bootstrapping: Methods and Design Principles Bisio, Ambra; Nolfi, Stefano; Tani, Jun. - 2016 BASE Show details 4 Humanoid infers Archimedes' principle: understanding physical relations and object affordances through cumulative learning experiences Bhat, Ajaz Ahmad; Mohan, Vishwanathan; Sandini, Giulio; Morasso, Pietro. - : The Royal Society, 2016 Abstract: Emerging studies indicate that several species such as corvids, apes and children solve ‘The Crow and the Pitcher’ task (from Aesop's Fables) in diverse conditions. Hidden beneath this fascinating paradigm is a fundamental question: by cumulatively interacting with different objects, how can an agent abstract the underlying cause–effect relations to predict and creatively exploit potential affordances of novel objects in the context of sought goals? Re-enacting this Aesop's Fable task on a humanoid within an open-ended ‘learning–prediction–abstraction’ loop, we address this problem and (i) present a brain-guided neural framework that emulates rapid one-shot encoding of ongoing experiences into a long-term memory and (ii) propose four task-agnostic learning rules (elimination, growth, uncertainty and status quo) that correlate predictions from remembered past experiences with the unfolding present situation to gradually abstract the underlying causal relations. Driven by the proposed architecture, the ensuing robot behaviours illustrated causal learning and anticipation similar to natural agents. Results further demonstrate that by cumulatively interacting with few objects, the predictions of the robot in case of novel objects converge close to the physical law, i.e. the Archimedes principle: this being independent of both the objects explored during learning and the order of their cumulative exploration. URL: https://doi.org/10.1098/rsif.2016.0310 http://repository.essex.ac.uk/24749/7/rsif.2016.0310.pdf http://repository.essex.ac.uk/24749/ BASE Hide details 5 Humanoid infers Archimedes' principle: understanding physical relations and object affordances through cumulative learning experiences Bhat, Ajaz Ahmad; Mohan, Vishwanathan; Sandini, Giulio. - 2016 BASE Show details 6 The ITALK project : A developmental robotics approach to the study of individual, social, and linguistic learning Gigliotta, Onofrio; Mohan, Vishwanathan; Nehaniv, C.L.. - 2015 BASE Show details 7 Embodied Language Learning and Cognitive Bootstrapping: Methods and Design Principles [Online resource] Zeschel, Arne; Lyon, Caroline; Nehaniv, Chrystopher L.. IDS-Repository Show details

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