Who Needs Emotions? The Brain Meets the Robot

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case, the computational processes must have some means for competing for
expression.
Based upon the use of common currency, Kismet’s architecture is implemented
as a value-based system. This simply means that each process computes
numeric values (in a common currency) from its inputs. These values
are passed as messages (or activation energy) throughout the network, either
within a system or between systems. Conceptually, the magnitude of
the value represents the strength of the contribution in influencing other
processes. Using a value-based approach has the effect of allowing influences
to be graded in intensity, instead of simply being on or off. Other processes
compute their relevance based on the incoming activation energies or messages
and use their computed activation level to compete with others for
exerting influence upon the other systems.
OVERVIEW OF THE COGNITIVE SYSTEM
The cognitive system is responsible for perceiving and interpreting events
and for arbitrating among the robot’s goal-achieving behaviors to address
competing motivations. There are two kinds of motivation modeled in Kismet.
The drives reside in the cognitive system and are modeled as homeostatic
processes that represent the robot’s “health” related goals. The emotive
system also motivates behavior, as described below (see Overview of the
Emotive System).
The computational subsystems and mechanisms that comprise the cognitive
system work in concert to decide which behavior to activate, at what
time, and for how long, to service the appropriate objective. Overall, the
robot’s behavior must exhibit an appropriate degree of relevance, persistence,
flexibility, and robustness. To achieve this, we based the design of the cognitive
system on ethological models of animal behavior (Gould, 1982). Below,
we discuss how Kismet’s emotion-inspired mechanisms further improve upon
the basic decision-making functionality provided by the cognitive system (see
Integrated Cognitive and Emotive Responses).
Perceptual Elicitors
Sensory inputs arising from the environment are sent to the perceptual system,
where key features are extracted from the robot’s sensors (cameras, microphones,
etc.). These features are fed into an associated releaser process. Each
releaser can be thought of as a simple perceptual elicitor of behavior that combines
lower-level features into behaviorally significant perceptual categories.