Article

Teaching neural networks using LEGO handy board robots in an artificial intelligence course

Author:

Susan P. ImbermanAuthors Info & Claims

SIGCSE '03: Proceedings of the 34th SIGCSE technical symposium on Computer science education

Pages 312 - 316

https://doi.org/10.1145/611892.611995

Published: 11 January 2003 Publication History

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Abstract

In this paper we propose a novel method for teaching neural networks with back propagation in an undergraduate Artificial Intelligence course. We use an agent based approach in the course, as outlined in the textbook Artificial Intelligence A Modern Approach by Stuart Russell and Peter Norvig [7]. The students build a robot agent whose task is to learn path-following behavior with a neural network. Robot agents are constructed from standard LEGO pieces and use the MIT Handy Board as a controller.

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Generation5.org, Back-Propagation: CBPNet, http://www.generation5.org/cbpnet.shtml

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Interactive C 4.0, Kiss Institute, Available WWW. http://www.kipr.org/ic/download/

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Kumar, D. and Meeden, L., A Robot Laboratory For Teaching Artificial Intelligence, In Proceedings of the 29th SIGCSE Technical Symposium on Computer Science Education (1998).

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Martin, F., The Handy Board. Available WWW. http://www.handyboard.com/

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Mitchell, T., Machine Learning, The McGraw Hill Companies Inc., 1997 ISBN 0-07-042807-7

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[7]

Russell, S., and Norvig, P., Artificial Intelligence A Modern Approach, Prentice-Hall Inc. 1995 ISBN 0-13-103805-2

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Sondak, N.E., Sondak, V. K., Neural Networks and Artificial Intelligence, In Proceedings of the 20th SIGCSE Technical Symposium on Computer Science Education February (1989).

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Using Interactive C 4.0, Available WWW. http://domanski.cs.csi.cuny.edu/imberman/csc126/startinginteractiveC40.htm

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Cited By

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Özkan SToz M(2022)A review study on the investigation of the effects of using robots in education on metacognitive behaviorsComputer Applications in Engineering Education10.1002/cae.2250830:4(1277-1288)Online publication date: 20-Mar-2022
https://doi.org/10.1002/cae.22508
Miller DNourbakhsh ISiegwart R(2008)Robots for EducationSpringer Handbook of Robotics10.1007/978-3-540-30301-5_56(1283-1301)Online publication date: 2008
https://doi.org/10.1007/978-3-540-30301-5_56
Imberman SKlibaner R(2005)A robotics lab for CS1Journal of Computing Sciences in Colleges10.5555/1089053.108907121:2(131-137)Online publication date: 1-Dec-2005
https://dl.acm.org/doi/10.5555/1089053.1089071
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Teaching neural networks using LEGO handy board robots in an artificial intelligence course

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An intelligent agent approach for teaching neural networks using LEGO® handy board robots
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In this article we describe a project for an undergraduate artificial intelligence class. The project teaches neural networks using LEGO® handy board robots. Students construct robots with two motors and two photosensors. Photosensors provide readings ...
Teaching neural networks using LEGO handy board robots in an artificial intelligence course

In this paper we propose a novel method for teaching neural networks with back propagation in an undergraduate Artificial Intelligence course. We use an agent based approach in the course, as outlined in the textbook Artificial Intelligence A Modern ...
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Published In

SIGCSE '03: Proceedings of the 34th SIGCSE technical symposium on Computer science education

February 2003

444 pages

ISBN:158113648X

DOI:10.1145/611892

Conference Chair:
Scott Grissom
Grand Valley State University
,
Program Chairs:
Deborah Knox
The College of New Jersey
,
Dan Joyce
Villanova University
,
Publications Chair:
Wanda Dann
Ithaca College

ACM SIGCSE Bulletin Volume 35, Issue 1
January 2003
406 pages
ISSN:0097-8418
DOI:10.1145/792548
Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 January 2003

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February 19 - 23, 2003

Navada, Reno, USA

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Overall Acceptance Rate 1,595 of 4,542 submissions, 35%

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Cited By

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Özkan SToz M(2022)A review study on the investigation of the effects of using robots in education on metacognitive behaviorsComputer Applications in Engineering Education10.1002/cae.2250830:4(1277-1288)Online publication date: 20-Mar-2022
https://doi.org/10.1002/cae.22508
Miller DNourbakhsh ISiegwart R(2008)Robots for EducationSpringer Handbook of Robotics10.1007/978-3-540-30301-5_56(1283-1301)Online publication date: 2008
https://doi.org/10.1007/978-3-540-30301-5_56
Imberman SKlibaner R(2005)A robotics lab for CS1Journal of Computing Sciences in Colleges10.5555/1089053.108907121:2(131-137)Online publication date: 1-Dec-2005
https://dl.acm.org/doi/10.5555/1089053.1089071
Imberman S(2005)Three fun assignments for an Artificial Intelligence classJournal of Computing Sciences in Colleges10.5555/1089053.108906921:2(113-118)Online publication date: 1-Dec-2005
https://dl.acm.org/doi/10.5555/1089053.1089069
Goldrick CHuggard M(2004)Peer learning with lego mindstorms34th Annual Frontiers in Education, 2004. FIE 2004.10.1109/FIE.2004.1408740(1198-1203)Online publication date: 2004
https://doi.org/10.1109/FIE.2004.1408740
Özkan SToz M(2022)A review study on the investigation of the effects of using robots in education on metacognitive behaviorsComputer Applications in Engineering Education10.1002/cae.2250830:4(1277-1288)Online publication date: 20-Mar-2022
https://doi.org/10.1002/cae.22508
Williams RPark HOh LBreazeal C(2019)PopBotsProceedings of the Thirty-Third AAAI Conference on Artificial Intelligence and Thirty-First Innovative Applications of Artificial Intelligence Conference and Ninth AAAI Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v33i01.33019729(9729-9736)Online publication date: 27-Jan-2019
https://dl.acm.org/doi/10.1609/aaai.v33i01.33019729
Sisman BGunay DKucuk S(2018)Development and validation of an educational robot attitude scale (ERAS) for secondary school studentsInteractive Learning Environments10.1080/10494820.2018.1474234(1-12)Online publication date: 13-May-2018
https://doi.org/10.1080/10494820.2018.1474234
Straub JKerlin SKim E(2017)Analysis of student characteristics and feeling of efficacy in a first undergraduate artificial intelligence course2017 IEEE International Conference on Electro Information Technology (EIT)10.1109/EIT.2017.8053322(010-015)Online publication date: May-2017
https://doi.org/10.1109/EIT.2017.8053322
Stansbury R(2010)Enhancing student learning in artificial intelligence using roboticsProceedings of the IEEE SoutheastCon 2010 (SoutheastCon)10.1109/SECON.2010.5453897(168-171)Online publication date: Mar-2010
https://doi.org/10.1109/SECON.2010.5453897
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An intelligent agent approach for teaching neural networks using LEGO® handy board robots

Teaching neural networks using LEGO handy board robots in an artificial intelligence course

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