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ERIC Number: EJ1207592
Record Type: Journal
Publication Date: 2019
Pages: 14
Abstractor: As Provided
ISSN: ISSN-1049-4820
Teaching Machine Learning in Robotics Interactively: The Case of Reinforcement Learning with Lego® Mindstorms
Martínez-Tenor, Ángel; Cruz-Martín, Ana; Fernández-Madrigal, Juan-Antonio
Interactive Learning Environments, v27 n3 p293-306 2019
Preparing students for dealing with a world more and more densely populated with physical machines that possess learning capabilities, e.g. intelligent robots, is of the utmost importance in engineering. In this paper, we describe and analyse a design of interactive sessions devoted to the application of some machine learning (ML) methods within a master degree subject named "Cognitive Robotics", in particular, reinforcement learning (RL), a technique that allows the machine to autonomously learn decision-making in a physical environment. The paper contains a complete depiction of the interactive teaching sessions, implemented with reasonable cost and resources thanks to a suitable mixture of the constructivist and instructivist paradigms. It also gathers the experiences of students and teachers through both qualitative and quantitatively indicators.
Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site:
Publication Type: Journal Articles; Reports - Descriptive
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Spain