The work depicted here was sponsored
by the U.S. Army and the Air Force Office of Scientific Research. Statements
and opinions expressed do not necessarily reflect the position or the policy
of the U.S. government, and no official
endorsement should be inferred.
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emotion, and model-driven experimentation—continue to shape our
research, yet other approaches may
be better suited, depending on one’s
underlying reason for exploring emotion; for example, models designed
to inform intelligent systems might
avoid some of the seemingly irrational
application of coping humans adopt.
Over the past half-century, there has
been rapid growth of cross-disciplin-ary research employing computational methods to understand human behavior, as well as facilitate interaction
between people and machines, with
work on computational models of
emotion becoming an important component. At times neglected in work in
cognitive science and AI, modern research in human emotion has firmly
established the powerful role emotion
plays in human behavior. As a consequence, researchers have turned to
computational models of emotion
as tools to research human emotion,
as well as exploit it in applications.
Here, we have sought to illustrate the
various ways such models are being
used, from a communitywide general
perspective to providing more specific
details from our own work on EMA.
Modeling appraisal theory in an
agent provides an interesting perspective on the relation between emotion
and rationality. Appraisal theory argues that emotion serves to generalize stimulus response by providing
more general ways to characterize
types of stimuli in terms of classes
of viable organism responses. For an
agent, appraisal dimensions serve a
general, uniform value function that
establishes the personal and social
significance of events. Assessments
(such as desirability, coping potential,
unexpectedness, and causal attribution) are clearly relevant to any social
agent, whether deemed emotional or
not. Having been characterized in a
uniform fashion, the appraisal results
coordinate systemwide coping responses that serve to guide the agent’s
specific responses to the eliciting
event, essentially helping the agent
find its ecological niche. Emotion is
thus inextricably coupled to how an
agent—human or artificial—reacts
and responds to the world.
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Stacy Marsella ( firstname.lastname@example.org) is a
professor of computer science and psychology at
Northeastern University, Boston, MA.
Jonathan Gratch ( email@example.com) is a professor of
computer science and psychology at the University of
Southern California, Los Angeles, CA.
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