Peter Stone's Selected Publications

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Layered Learning on a Physical Robot

Peggy Fidelman and Peter Stone. Layered Learning on a Physical Robot. In Under Review. , February 2005.
Some videos of the robot referenced in the paper.

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Abstract

Layered learning is a general hierarchical machine learning paradigm that leverages a given task decomposition to learn complex tasks efficiently. Though it has been validated previously in simulation, this paper presents the first application of layered learning on a physical robot. In particular, it enables the learning of a high-level grasping behavior that relies on a gait which itself must be learned. All learning is done autonomously onboard a commercially available Sony Aibo robot, with no human intervention other than battery changes. We demonstrate that our approach makes it possible to quickly learn both a fast gait and a reliable grasping behavior which, in combination, significantly outperform our best hand-tuned solution.

BibTeX Entry

@InProceedings(IROS2005-chinpinch,
        author="Peggy Fidelman and Peter Stone",
        title="Layered Learning on a Physical Robot",
        booktitle="Under Review.  ",
        month="February",year="2005",
        abstract={
                  Layered learning is a general hierarchical machine
                  learning paradigm that leverages a given task
                  decomposition to learn complex tasks efficiently.
                  Though it has been validated previously in
                  simulation, this paper presents the first
                  application of layered learning on a physical robot.
                  In particular, it enables the learning of a
                  high-level grasping behavior that relies on a gait
                  which itself must be learned.  All learning is done
                  autonomously onboard a commercially available Sony
                  Aibo robot, with no human intervention other than
                  battery changes.  We demonstrate that our approach
                  makes it possible to quickly learn both a fast gait
                  and a reliable grasping behavior which, in
                  combination, significantly outperform our best
                  hand-tuned solution.
        },
        wwwnote={Some <a href="http://www.cs.utexas.edu/users/AustinVilla/?p=research/learned_acquisition">videos of the robot</a> referenced in the paper.},
)

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