Abstract:
Automatic transfer of learned knowledge from one task or
domain to another offers great potential to simplify and expedite
the construction and deployment of intelligent systems.
In practice however, there are many barriers to achieving this
goal. In this article, we present a prototype system for the
real-world context of transferring knowledge of American
football from video observation to control in a game simulator.
We trace an example play from the raw video through execution
and adaptation in the simulator, highlighting the system’s
component algorithms along with issues of complexity,
generality, and scale. We then conclude with a discussion
of the implications of this work for other applications, along
with several possible improvements.
Description:
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