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

Susan P. Imberman | Zendy

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

Author(s) -

Susan P. Imberman

Publication year - 2003

Publication title -

proceedings of the 35th sigcse technical symposium on computer science education

Language(s) - English

Resource type - Conference proceedings

DOI - 10.1145/611892.611995

Subject(s) - robot , artificial neural network , artificial intelligence , course (navigation) , computer science , task (project management) , path (computing) , engineering , systems engineering , programming language , aerospace engineering

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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