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@InProceedings(AAAI04,
        author="Nate Kohl and Peter Stone",
        title="Machine Learning for Fast Quadrupedal Locomotion",
        year="2004",month="July",
        booktitle="The Nineteenth National Conference on Artificial Intelligence",
        pages="611--616",
        abstract={
                  For a robot, the ability to get from one place to
                  another is one of the most basic skills.  However,
                  locomotion on legged robots is a challenging
                  multidimensional control problem.  This paper
                  presents a machine learning approach to legged
                  locomotion, with all training done on the physical
                  robots.  The main contributions are a specification
                  of our fully automated learning environment and a
                  detailed empirical comparison of four different
                  machine learning algorithms for learning quadrupedal
                  locomotion.  The resulting learned walk is
                  considerably faster than all previously reported
                  hand-coded walks for the same robot platform.
                  },
        wwwnote={Some <a href="http://www.cs.utexas.edu/users/AustinVilla/legged/learned-walk/">videos of walking robots</a> referenced in the paper.<br>
                 <a href="http://www.aaai.org/Conferences/National/2004/aaai04.html">AAAI 2004</a>},
)