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このアイテムの引用には次の識別子を使用してください: http://hdl.handle.net/10119/14233

タイトル: Long-term Knowledge Acquisition in a Memory-based Epigenetic Robot Architecture for Verbal Interaction
著者: Pratama, Ferdian
Mastrogiovanni, Fulvio
Jeong, Sungmoon
Chong, Nak Young
キーワード: human-robot interaction
memory-based architecture
contextual information
developmental robotics
verbal interaction
発行日: 2015
出版者: Institute of Electrical and Electronics Engineers (IEEE)
誌名: 2015 24th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)
開始ページ: 25
終了ページ: 30
DOI: 10.1109/ROMAN.2015.7333563
抄録: We present a robot cognitive framework based on (a) a memory-like architecture; and (b) the notion of “context”. We posit that relying solely on machine learning techniques may not be the right approach for a long-term, continuous knowledge acquisition. Since we are interested in long-term human-robot interaction, we focus on a scenario where a robot “remembers” relevant events happening in the environment. By visually sensing its surroundings, the robot is expected to infer and remember snapshots of events, and recall specific past events based on inputs and contextual information from humans. Using a COTS vision frameworks for the experiment, we show that the robot is able to form “memories” and recall related events based on cues and the context given during the human-robot interaction process.
Rights: This is the author's version of the work. Copyright (C) 2015 IEEE. 2015 24th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 2015, 25-30. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
URI: http://hdl.handle.net/10119/14233
資料タイプ: author
出現コレクション:b11-1. 会議発表論文・発表資料 (Conference Papers)

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