Shallow Blue: Lego-Based Embodied AI as a Platform for Cross-Curricular Project Based Learning
Abstract
We report on Shallow Blue (SB), an autonomous chess agent constructed by a small group of faculty and undergraduate students at Canisius College. In addition to pushing the limits of consumer grade components at low cost, SB is a focal point for interdisciplinary student projects spanning computer science, engineering, and physics. We demonstrate that undergraduate students can engage in rich, long-term robotic design and applied Artificial Intelligence (AI) from both hardware and software perspectives. Student outcomes of SB include senior theses, conference presentations, peer-reviewed publications, and admission to graduate programs. Students who participated also report substantial development in skills and knowledge applicable to their post-undergraduate education and careers.
Cite
Text
Selkowitz and Burhans. "Shallow Blue: Lego-Based Embodied AI as a Platform for Cross-Curricular Project Based Learning." AAAI Conference on Artificial Intelligence, 2014. doi:10.1609/AAAI.V28I3.19040Markdown
[Selkowitz and Burhans. "Shallow Blue: Lego-Based Embodied AI as a Platform for Cross-Curricular Project Based Learning." AAAI Conference on Artificial Intelligence, 2014.](https://mlanthology.org/aaai/2014/selkowitz2014aaai-shallow/) doi:10.1609/AAAI.V28I3.19040BibTeX
@inproceedings{selkowitz2014aaai-shallow,
title = {{Shallow Blue: Lego-Based Embodied AI as a Platform for Cross-Curricular Project Based Learning}},
author = {Selkowitz, Robert and Burhans, Debra T.},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2014},
pages = {3037-3049},
doi = {10.1609/AAAI.V28I3.19040},
url = {https://mlanthology.org/aaai/2014/selkowitz2014aaai-shallow/}
}