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Creating Relationships with Computers and Robots 13

feedback gained to design artifacts which are more socially competent in the
future. Sparky is not autonomous but teleoperated, since the current state of the
art in mobile and social robotics does not permit to achieve complex and rich
enough interactions. In addition to facial expression, Sparky makes extensive
use of its body (e.g., posture, movement, eye tracking, mimicry of people’s
motions) to express emotion and to interact with humans. The authors report
and discuss very interesting observations of people interacting with the robot,
as well as the feedback provided in interviews with some of the participants in
the experiments and with the operators of Sparky.

2.6 Interactive Education and Training

Virtual training environments can provide (compared with field studies) very
cost-efficient training scenarios that can be experimentally manipulated and
closely monitor a human’s learning process. Clearly, interactive virtual train-
ing environments are potentially much more ‘engaging’ in contrast to non-
interactive training where relevant information is provided passively to the
user, e.g. in video presentations. The range of potential application areas is
vast, but most promising are scenarios that would otherwise (in real life) be
highly dangerous, cost-intensive, or demanding on equipment.
Similarly, Socially Intelligent Agents in children’s (or adult’s) education can
provide enjoyable and even entertaining learning environments, where children
learn constructively and cooperatively. Such learning environments cannot re-
place ‘real life’ practical experience, but they can provide the means to cre-
atively and safely explore information and problem spaces as well as fantasy
worlds. Using such environments in education also provides useful computer
skills that the children acquire ‘by doing’. Education in such systems can range
from learning particular tasks (such as learning interactively about mathemat-
ics or English grammar), encouraging creativity and imagination (e.g. through
the construction of story environments by children for children), to making a
contribution to personal and social education, such as getting to know different
cultures and learning social skills in communication, cooperation and collabo-
ration with other children that might not be encountered easily in real life (e.g.
children in other countries).
In chapter 22 Jonathan Gratch describes ‘socially situated planning’ for de-
liberate planning agents that inhabit virtual training environments. For training
simulators, in order to be believable, not only the physical dynamics, but also
the social dynamics and the social behavior of the agents must be designed
carefully. For learning effects to occur, such training scenarios need to be ‘re-
alistic’ and believable enough to engage the user, i.e. to let the user suspend
the disbelief that this is not ‘just a simulation’ where actions do not matter. In
the proposed architecture, social reasoning is realized as a meta-level on top