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

Authors:
Susan P. Imberman
Affiliations:
College of Staten Island, City University of New York, Staten Island, NY
Venue:
SIGCSE '03 Proceedings of the 34th SIGCSE technical symposium on Computer science education
Year:
2003

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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.