Creating New Informational Primitives in Minds and Machines - Computers and Creativity - page 389

Table 15.1 Modes of creativity with respect to semiotic dimensions

Type of system
Stable
Maintain structure

Aspect Primitives

Combinatoric
Search existing
possibilities

Creative
Add possibilities

Syntactic Sign-states &

computations

Deterministic
finite-state automata

Adaptive changes in
state-transition rules
trainable machines

Evolve new states &
rules growing automata

Semantic Measurements

& actions

Fixed sensors &
effectors (fixed
robots)

Adaptive search for
optimal combinations
of existing sensors &
effectors

Evolve new
observables, actions
epistemic autonomy

Pragmatic Goals Fixed goals Search combinations

of existing goals
adaptive priorities

Evolve new goals
creative self-direction
motivational autonomy

15.3.3 Capabilities and Limitations of Adaptive Devices

One can consider the capabilities and limitations of devices with computational
coordinative parts, sensors, effectors, and goal-directed mechanisms for adaptive
steering and self-construction (Fig. 15.3 ). For the sake of simplicity, we will think
of these systems as robotic devices with sensors and effectors whose moment-to-
moment behaviour is controlled by a computational part that maps sensory inputs to
action decisions and motor outputs. In biological nervous systems these coordinative
functions are carried out by analog and mixed analog-digital neural mechanisms.
Purely computational devices (top left) deterministically map symbolic, input
states to output states, i.e. they are formally equivalent to deterministic finite state
automata. As they have no non-arbitrary linkages to the external world, their internal
states have no external semantics save those that their human programmer-users
assign to them. Because their computational part is fixed and functionally stable,
such devices are completely reliable. However, they are not creative in that they
cannot autonomously generate either new combinations (input-output mappings) or
new primitives (sign states).
Some of the functional limitations of formal systems and computational devices
are due to their purely syntactic nature, that the sign-states lack intrinsic seman-
tics or pragmatics. The signs and operations are meaningless and purposeless, aside
from any meanings or purposes that might be imposed on them by their users. Other
limitations arise from their fixed nature, that pure computations do not receive con-
tingent inputs from outside the sign-system, and therefore have no means of adap-
tively adjusting their internal operations—they do not learn.
One might retort that we have all sorts of computers that are constantly receiv-
ing updates from external sources and adjust their behaviour accordingly, but the
moment a machine acts in manner that depends not only on its initial state and
state-transition rules, its behaviour is no longer a pure computation—it is no longer