Who Needs Emotions? The Brain Meets the Robot

358 conclusions
explicitly formal representation of the underlying dynamics to explain how
motivation affects the way in which an animal will move around its environment.
For Watts, interactions of sensory information, arousal state, and
interoceptive information determine the value of various drives; the integration
of competing drives, presumably via complex sets of projections from
the hypothalamus, then determines which series of actions will generate the
most appropriate procurement (or appetitive) phase, where the goal object
which will reduce the drive intensity is actively sought. The motor events
expressed during the procurement phase involve foraging behavior, are individualized
for the particular situation, and can be quite complex. When
the goal object has been located, the subsequent consummatory phase involves
more stereotypic rhythmic movements—licking, chewing, copulating, etc.—
that allow the animal to interact directly with the goal object. Watts also
notes that interactions between different drive networks, particularly in the
hypothalamus, are of paramount importance. For example, the effects of
starvation are not limited to increasing the drive to eat but also include reduced
reproductive capacity. Similarly, dehydration leads to severe anorexia
as well as increased drive to drink (Watts, 2001). This cross-behavioral coordination
is part of the mechanism that selects the drive with the highest
priority and most likely involves hormonal modulation acting together with
the divergent neuroanatomical outputs from individual drive networks. As
Watts notes, the notions of drive and that particular behaviors are selected
to reduce the level of specific drive states have been very influential in neuroscience
but remain somewhat controversial.
Arbib and Lieblich (1977) represented the animal’s knowledge of its
world in a structure they called the “world graph” (WG), a set of nodes connected
by a set of edges, where the nodes represent places or situations recognized
by the animal, and the links represent ways of moving from one
situation to another. A crucial notion is that a place encountered in different
circumstances may be represented by multiple nodes but that these nodes
may be merged when the similarity between these circumstances is recognized.
They model the process whereby the animal decides where to move
next, on the basis of its current drive state (hunger, thirst, fear, etc.) and
how the WG may itself be updated in the process. The model includes the
effects of incentive (e.g., sight or smell of food) as well as drives (e.g., hunger)
to show how a route, possibly of many steps, that leads to the desired
goal may be chosen and how short cuts may be chosen. Perhaps the most
important feature of their model is their description of what drive-related
information is appended to the nodes of the WG and how the WG changes
over time. They postulate that each node x of WG(t) is labeled with the
vector [R(d 1,x,t) . . . R(d k,x,t)] of the animal’s current expectations at time
t about the drive-related properties of the place or situation P(x) represented