Who Needs Emotions? The Brain Meets the Robot

architectural basis of affect 207
desires, plans, decisions, and inferences, which are not physical objects or processes
but are implemented in physical mechanisms, such as brains. 1
Information-processing virtual machines can vary in many dimensions,
for example, the number and variety of their components, whether they use
discretely or continuously variable substates, whether they can cope with
fixed or variable complexity in information structures (e.g., vectors of values
versus parse trees), the number and variety of sensors and effectors, how
closely internal states are coupled to external processes, whether processing
is inherently serial or uses multiple concurrent and possibly asynchronous
subsystems, whether the architecture itself can change over time, whether
the system builds itself or has to be assembled by an external machine (like
computers and most current software), whether the system includes the
ability to observe and evaluate its own virtual-machine processes or not (i.e.,
whether it includes “meta-management” as defined by Beaudoin, 1994),
whether it has different needs or goals at different times, how conflicts are
detected and resolved, and so on.
In particular, whereas the earliest organisms had sensors and effectors
directly connected so that all behaviors were totally reactive and immediate,
evolution “discovered” that, for some organisms in some circumstances,
there are advantages in having an indirect causal connection between sensed
needs and the selections and actions that can be triggered to meet the needs,
i.e., an intermediate state that “represents” a need and is capable of entering
into a wider variety of types of information processing than simply triggering
a response to the need.
Such intermediate states could allow (1) different sensors to contribute
data for the same need; (2) multifunction sensors to be redirected to gain
new information relevant to the need (looking in a different direction to check
that enemies really are approaching); (3) alternative responses to the same
need to be compared; (4) conflicting needs to be evaluated, including needs
that arise at different times; (5) actions to be postponed while the need is
remembered; (6) associations between needs and ways of meeting them to
be learned and used, and so on.
This seems to capture the notion of a system having goals as well as needs.
Having a goal is having an enduring representation of a need, namely, a representation
that can persist after sensor mechanisms are no longer recording the
need and that can enter into diverse processes that attempt to meet the need.
Evolution also produced organisms that, in addition to having need sensors,
had fact sensors that produced information that could be used for
varieties of needs, i.e., “percepts” (closely tied to sensor states) and “beliefs,”
which are indirectly produced and can endure beyond the sensor states that
produce them.