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Fig. 15.5
Emergence relative-to-a-model. What changes need to be adopted by an observer in
order to continue to predictively track the behaviour of an evolving, complexifying system?
part, and effectors, the computational part of the device that mapped sensory inputs
into motor commands would have state-determined transitions.
One can determine if the input-output mapping of the computational part has
changed by observing its state-transition structure (Fig.
15.5
, top panel). If the com-
putational part is a fixed program, this sensorimotor mapping will remain invariant.
If the computational part is switched by some adaptive process, as in a trainable
machine, then the sensorimotor mapping will change with training, and a new deter-
minate input-output state transition behaviour will then ensue. From an observer's
perspective, the predictive model will fail every time training alters the computa-
tional sensorimotor mapping. In order to recover predictability, the observer would
have to change the state-transition rules of his or her predictive model. Thus an
observer can determine whether the device under observation is performing fixed
computations or whether these are being adjusted in some way over time.
Similarly, if the device evolves a new sensor, such that its behaviour becomes
dependent on factors that are not registered in the observer's set of measurements,
