An intelligent agent approach for teaching neural networks using LEGO® handy board robots

ABSTRACT

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 that act as inputs for the neural network. Output values power the motors and maintain the robot along the designated path. In doing this project, students come to realize the difference between training a neural network and the trained neural network. The fun factor associated with this project has encouraged students to elect artificial intelligence as part of their course of study.

REFERENCES

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.6 Learning
          Subjects: Connectionism and neural nets

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.9 Robotics
          Subjects: Autonomous vehicles

  K. Computing Milieux
  K.3 COMPUTERS AND EDUCATION
      K.3.2 Computer and Information Science Education
          Subjects: Computer science education

General Terms:
Algorithms, Design, Experimentation, Human Factors

Keywords:
artificial intelligence, back propagation, handy board, neural networks, robotics