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Who Needs Emotions? The Brain Meets the Robot

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206 robots<br />

some cases and in o<strong>the</strong>r cases deliberative, i.e., mediated by a mechanism<br />

that represents possible sequences of actions, compares <strong>the</strong>m, evaluates <strong>the</strong>m,<br />

and makes selections on that basis before executing <strong>the</strong> actions.<br />

We can distinguish sensors that act as need-sensors from those that act<br />

as fact-sensors. Need-sensors have <strong>the</strong> function of initiating action or tending<br />

to initiate action (in contexts where something else happens to get higher<br />

priority) to address a need, whereas fact-sensors do not, though <strong>the</strong>y can<br />

modify <strong>the</strong> effects of need sensors. For most animals, merely sensing <strong>the</strong> fact<br />

of an apple on a tree would not in itself initiate any action relating to <strong>the</strong><br />

apple. However, if a need for food has been sensed, <strong>the</strong>n that will (unless<br />

overridden by ano<strong>the</strong>r need) initiate a process of seeking and consuming food.<br />

In that case, <strong>the</strong> factual information about <strong>the</strong> apple could influence which<br />

food is found and consumed.<br />

<strong>The</strong> very same fact-sensor detecting <strong>the</strong> very same apple could also<br />

modify a process initiated by a need to deter a predator; in that case, <strong>the</strong><br />

apple could be selected for throwing at <strong>the</strong> predator. In this case, we can say<br />

that <strong>the</strong> sensing of <strong>the</strong> apple has no motivational role. It is a “belief-like” state,<br />

not a “desire-like” state.<br />

INFORMATION-PROCESSING ARCHITECTURES<br />

<strong>The</strong> information-processing architecture of an organism or o<strong>the</strong>r object is <strong>the</strong><br />

collection of information-processing mechanisms that toge<strong>the</strong>r enable it to<br />

perform in such a way as to meet its needs (or, in “derivative” cases, could<br />

enable it to meet <strong>the</strong> needs of some larger system containing it).<br />

Describing an architecture involves (recursively) describing <strong>the</strong> various<br />

parts and <strong>the</strong>ir relationships, including <strong>the</strong> ways in which <strong>the</strong>y cooperate or<br />

interfere with one ano<strong>the</strong>r. Systems for which <strong>the</strong>re are such true collections<br />

of statements about what <strong>the</strong>y would do to meet needs under various<br />

circumstances can be described as having control states, of which <strong>the</strong> belieflike<br />

and desire-like states mentioned previously (and defined formally below)<br />

are examples. In a complex architecture, <strong>the</strong>re will be many concurrently<br />

active and concurrently changing control states.<br />

<strong>The</strong> components of an architecture need not be physical: physical mechanisms<br />

may be used to implement virtual machines, in which nonphysical structures<br />

such as symbols, trees, graphs, attractors, and information records are<br />

constructed and manipulated. This idea of a virtual machine implemented in<br />

a physical machine is familiar in computing systems (e.g., running word processors,<br />

compilers, and operating systems) but is equally applicable to organisms<br />

that include things like information stores, concepts, skills, strategies,

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