When an M-model is activated it does not know how many entities are in the
external reality. Even more, it does not know which are these entities. The
device will try to find them based on the facilities of the sense organs, but
there is no guarantee that M-models have found all the entities and no
guarantee that the right YMs are associated to such entities. This is a basic
deficiency.
The camouflage and dissimulation are methods which use this deficiency. By
camouflage an entity is not discovered and by dissimulation M-models associate
a wrong YM to an entity.
Let's see another basic problem. Any model evolves to be harmonic with itself
and so, to be stable. This means that, after any change in the model, it has
to regain its stability. If a model has a disharmony, it has to correct itself
based on IR or based on an internal change (IR is not available in any
situation). Thus the model regains its stability, but in some cases the model
could be not suitable anymore to reflect the external reality. There are many
cases when a model is stable but its predictions associated with the external
reality are wrong.
We already defined reality as all the information that is or could be
generated by a model by simulation. The guarantee of a correct reality is the
stability of the model but the stability of the model is not a guarantee that
the model is capable to accurately reflect the associated external reality.
That is, there is no guarantee that all the entities of a given external
reality are discovered, there is no guarantee that the right YMs are
associated with these entities and so on. The stability of a model is just a
guarantee that all the available information is correlated in the right way.
There is another class of basic problems associated with the changes in a
model. If a model has to be changed, sometimes there are small chances to do
that. In fact, the only possibility is to make a new model from scratch, using
or not elements and relations from the old model. This activity could be
sometimes so complex that it can exceed the technical capacity of the brain.
Indeed, a new model must be accepted by the whole structure of models. That
is, any other model of the structure must accept any prediction of the new
model, so that the new structure is stable.
If the new model is good in interaction with the external reality but the
structure of the models is not good enough, then some other models of the
structure have to be changed too. As I said, this process can exceed the
brain's technical capacity of processing. This can be considered as a design
deficiency too.
This explains a lot of situations in common life, when logical arguments or
facts taken from external reality cannot change wrong models some people have.
As we know, a stable model is a model which correlates in a right way all the
available information. But, there is no guarantee that we gain enough
information to make the right model. This basic deficiency is attenuated by
the fact that there is a structure of models. The structure of models helps a
lot when we interact with a new external reality because it can make
predictions based on the previous interaction with other external realities.
On the other hand, the structure of models is like a brake for evolution if
the structure has problems.
Example: The astronomer Copernicus made a model of the Universe based on the
idea that the Sun is the center of the Universe, not Earth, as everybody knew
at the time. Around the year 1543, very few persons were able to change the
whole structure of models, based on this new model.
We continue with other basic problems and features.
In the normal activity of the brain, any ZM-model has full access to any model
of the brain. That is, a ZM model can correlate information from many M-type
models and from any other ZM of the brain. This is true for any ZM of the
brain.
In the complex interaction between a brain and the external reality, there is
a single ZM at a time, controlling that being. This ZM is called a local-ZM or
an active-ZM. A ZM can be changed to another in a dynamical way, so that the
being does many activities in time-sharing.
This activity is not simple. So, when a local-ZM is deactivated, it has to
store the conditions, to be able to resume when it takes control again. There
are problems associated with this activity. Some of the information can be
lost or the external reality may evolve in the mean time so that the stored
information will be of no use. In this way, any model, which takes control of
the being, has to initialize before being able to regain full control. This
activity of initialization is very complex and in some situations it might
contain errors. Thus, it is rather difficult to do many activities in time-
sharing.
There is also a basic problem associated with the term "knowledge". As we
know, the knowledge is associated with the predictions of a structure of
models.
So, the knowledge is associated with the structure of models and not with the
external reality, as we'd like it to be. We should never ever forget this
thing. Even more, knowledge is a non-sense if we do not declare the structure
of models.
Example: in any positive science, it is usual to say that something is true
based on a specified theory (model).