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Exploration and exploitation of sensorimotor contingencies for a cognitive embodied agent

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Details

Original languageEnglish
Title of host publicationICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence
EditorsAna Rocha, Luc Steels, Jaap van den Herik
PublisherSCITEPRESS
Pages546-554
Number of pages9
Volume2
ISBN (Electronic)9789897583957
DOIs
Publication statusPublished - 2020
Publication typeA4 Article in a conference publication
EventInternational Conference on Agents and Artificial Intelligence -
Duration: 1 Jan 1900 → …

Conference

ConferenceInternational Conference on Agents and Artificial Intelligence
Period1/01/00 → …

Abstract

The modelling of cognition is playing a major role in robotics. Indeed, robots need to learn, adapt and plan their actions in order to interact with their environment. To do so, approaches like embodiment and enactivism propose to ground sensorimotor experience in the robot's body to shape the development of cognition. In this work, we focus on the role of memory during learning in a closed loop. As sensorimotor contingencies, we consider a robot arm that moves a baby mobile toy to get visual reward. First, the robot explores the continuous sensorimotor space by associating visual stimuli to motor actions through motor babbling. After exploration, the robot uses the experience from its memory and exploits it, thus optimizing its motion to perceive more visual stimuli. The proposed approach uses Dynamic Field Theory and is integrated in the GummiArm, a 3D printed humanoid robot arm. The results indicate a higher visual neural activation after motion learning and show the benefits of an embodied babbling strategy.

ASJC Scopus subject areas

Keywords

  • Cognitive Robotics, Dynamic Neural Fields, Embodiment, Sensorimotor Contingencies

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Field of science, Statistics Finland

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