Who Needs Emotions? The Brain Meets the Robot

240 robots
some undesirable emotional states to be hard to avoid in certain contexts if
the machines have affective control mechanism that interact in complex
ways.
Detailed studies of design and niche space, in which the relationships
between classes of designs and classes of niches for these designs in a variety
of environments are investigated, should clarify the costs and benefits. For
this, we need experiments with agent architectures that complement theoretical,
functional analyses of control systems by systematic studies of
performance–cost tradeoffs, which will reveal utility or disadvantages of various
forms of control in various environments.
Finally, the main utility in AI of control systems producing states conforming
to our suggested definition of emotional does not lie in systems that
need to interact with humans or animals (e.g., by recognizing emotions in
others and displaying emotions to others). There is no reason to believe that
such control mechanisms (where something can modulate or override the
normal behavior of something else) are necessary to achieve “believable interactions”
among artifacts and humans. Large sets of condition–action rules,
for example, may produce convincing behavioral expressions that give the
appearance of sympathy or surprise without implementing the kinds of control
mechanism that we called “emotional.” Hence, such systems may appear
to be emotional without actually having emotions in our sense, but
appearances will suffice for many applications, especially in computer games
and entertainments, as they do in human stage performances and in cartoon
films.
In contrast, control mechanisms capable of producing states conforming
to our proposed definition of emotional will be useful in systems that need
to cope with dynamically changing, partly unpredictable and unobservable
situations where prior knowledge is insufficient to cover all possible outcomes.
Specifically, noisy and/or faulty sensors, inexact effectors, and insufficient
time to carry out reasoning processes are all limiting factors with which
real-world, real-time systems have to deal. As argued in Simon (1967/1979)
and Sloman & Croucher (1981), architectures for such systems will require
mechanisms able to deal with unexpected situations. In part, this trivializes
the claim that emotional controls are useful since they turn out to be instances
of very general requirements that are obvious to engineers who have
to design robust and “failsafe” systems to operate in complex environments.
What is nontrivial is which systems are useful in different sorts of architectures
and why.
There is much work in computer science and robotics that deals with
control systems that have some features in common with what we call affective
mechanisms, from real-time operating systems that use timers and
alarm mechanisms to achieve time-critical tasks to robot control systems that