Modeling the environment in control systems has been generally done up to the
extent of addressing the interference it produces in the performance of the task.
This can be as simple as statistically modeling an interfering disturbance in SISO
controllers (See Figure 2) or as complex as simultaneous localisation and mapping
in autonomous mobile robotics.
The question of modeling the system is trickier and will be the main focus of the
rest of this paper. Let’s say that in conventional analyses of control systems these
realisational aspects are comonly neglected or reduced to considerations concerning
design constraints derived from implementation limitations. The issue of embed-
ding system models —i.e. of the system knowing about its own body— has been
raised in many contexts but got wider audience in relation with robotics embodi-
ment considerations Chrisley and Ziemke (2002).
5 The Perceiving Agent
As deeply analised by Lopez Lopez (2007) there are strong differences between
sensing and perceiving, related to the expectation and model-driveness of this last
one.
The perceptual process is structured as a potentially complex pipeline of two
classes of processes that we could describe as sensor-driven and model-driven.
The perceptual pipeline can affect the perceiving system in two ways: implicitly,
through changes in operational states of other subsystems; and explicitly through
cognitive integration of what has been perceived into integrated representations.
This unified understanding of perception as a model-driven process Lopez et al.
(2007) leads to the introduction of a new principle:
Principle 5: Model-driven perception — Perception is the continuous up-
date of the integrated models used by the agent in a model-based cognitive
control architecture by means of real-time sensorial information.
This principle implies that the result of perception is not a scattered series of in-
dependent percepts, but these percepts fully incoprorated into an integrated model.
This means that it is possible to sense without actually perceiving; e.g. if the cogni-
tive —i.e. model-driven— sensory processing fails in the integration.
To be integrable, the percept must follow some rules that are captured both in the
mechanics of cognitive perception and in the set of referents used in the perception
process. The mechanics typically will form part of the permanent structure of the
agent while some of the referents may be part of its program (see Klir (1969) for
details on the duality structure/program).
Even more, the perception mechanism is not restricted to process information
coming from the environment of the perceiving system but can exploit also infor-
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