Handing over control: When it is better for an arti cial agent to let the human decide?
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2019-06-26
Language
en
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Abstract
This thesis considers human-robot collaborative scenarios, where the
agent can be in need of assistance from a human collaborator. As for
all autonomous systems, performance is very important. In addition to
performance, it is also desirable that a human-agent collaborative system
does not interrupt the human continuously: It needs to be able to pick
good moments to do so, in order to not interrupt the human collaborator,
while maintaining a good level of performance.
A collaborative chess game was implemented and used as an instrument
to conduct experiments. In this game, two agents play against each other.
One of these can decide to ask for help from an expert agent, based the
distribution of evaluation values given a state. Using this framework,
the research questions can be researched, pertaining to the level of per-
formance of asking for help versus not doing so and whether the timing
matters: We test this by comparing the performance of the former to an
agent that hands over control at random intervals, but at the same fre-
quency.
Experimental results showed that help-asking frequency in
uenced per-
formance and that the timing at which these help-calls were uttered were
important to the performance as well.
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Faculteit der Sociale Wetenschappen