Abstract
When someone says a statement about a particular subject, we memorize the assertion and, implicitly, we can construct all the possible questions that have as a right answer to the assertion just heard. This means that, in this specific case, our learning process based on assertions subsists. When we read a book, we do nothing but learn through a succession of assertions. In this article, we present a system for automatically constructing a conversational agent, which uses only assertions to build the dialog engine. The whole architecture is based on the “Robot Operating System” (ROS), and the experiments were conducted using a humanoid robot.
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In linguistics, WH-movement is about rules of syntax involving the placement of interrogative words, that is an asymmetry between the syntactical arrangement of words (morphemes) in a question and the form of answers to that question.
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Acknowledgements
This research was partially supported by the project AMICO - Assistenza Medicale In COntextual Awareness, with funding from the National Programs of the Italian Ministry of Education, Universities and Research (code: ARS01_00900).
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Maniscalco, U., Messina, A., Storniolo, P. (2020). An Automatic System for Learning and Dialogue Based on Assertions. In: Samsonovich, A. (eds) Biologically Inspired Cognitive Architectures 2019. BICA 2019. Advances in Intelligent Systems and Computing, vol 948. Springer, Cham. https://doi.org/10.1007/978-3-030-25719-4_44
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DOI: https://doi.org/10.1007/978-3-030-25719-4_44
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