Common basic knowledge for artificial intelligence algorithms

The not-exhaustive essence of this system shouldn't hide the intrinsic complexity of some of its ideas. This section has precisely to be understood as an additional support to help readers get a clearer picture; mainly about what was explained in the previous two sections (Defining principles & Data format). That's why these contents should never be taken as a step-by-step guide or a detailed example.

The table below shows (a very simplistic version of) the kind of information which the proposed system would have to bring into consideration in order to account for:

"a car is faster than a bicycle"

and

"a car is more dangerous to people than a bicycle"

Legend: car / bicycle \| both of them
Layers	Selected Enum Option	Properties	Property Contents	Connectors
L0 Function	understanding	P0 Dangerous to people	0 (not harmful) - 100 70 / 20	more than
L1 Speciality	common	P1 Speed	m/s minimum: 0 / 0 maximum: 16 / 120 typical: 9 / 28	less than
L2 Security	0 (no impact) - 100 70 / 40
L100 Staticity	mobile
L101 Machines	vehicle
L102 Environment	0 (very harmful) - 100 50 / 100

CLARIFICATIONS:

In a real scenario, much more information would have to be considered, even in case of only wanting to store the aforementioned two concepts. For example: additional Layers would be required and all of them would have to be properly defined; same ideas (i.e., additional ones and proper definitions) would have to be applied to Properties; just two Entities is not enough to adequately account for car and bicycle (i.e., there are many different types of cars and bicycles); etc.
In application of the Defining principles of this system, the exact format of each element has to be as variable (scalable and adaptable) as possible. For example, the Properties (and even the Layers) are applied by relying on a 0-100 scale (whose values are automatically calculated or manually input) or with certain descriptive values (e.g., maximum, minimum and most typical), as shown in the table. On the other hand, it has to be noted that any other suitable alternative (i.e., fully compatible with the remaining parts of the system) might also be considered.
Although the rankings may not be modified (except Ranking C, which is redefined on account of the Entity being considered), the scale-based definitions should be adapted to the exact conditions in order to accurately describe each situation. For example: the
"a car is faster than a bicycle"
Concept can be assessed by giving higher preference to the elements which are not harmful for the environment (
L102
as currently displayed) or right the contrary (by defining
0
in
L102
as
not harmful
).
There are certain parts which may not have the aforementioned flexibility. For example, the first layers (i.e.,
L0
,
L1
and
L2
in the table. Note that the number of these Layers is expected to be much bigger in a real scenario) will not be altered under any circumstance.

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Common basic knowledge for artificial intelligence algorithms