Chapter 12

1. The existence of a fundamental symbolic model called General Communication Language (GCL) is supposed. This symbolic model contains absolutely all words, together with their definitions. The definitions can be more or less precise, logically consistent or not, can be or not accepted by some or others. GCL is the common language formed spontaneously between people in their inter-relations along the milleniums. 2. We choose a word (term) T from GCL. 3. Let's suppose that there is a positive science SM, that could include the term T. 4. The term T, that should be studied by SM, has to be included in SM. For this purpose, T has to be redefined within the frame of SM. SM can integrate a new term only if this term is defined within SM. Thus T will have one definition in GCL and another generated by SM.

Example: The term 'force' has one definition in GCL and another in Newton's Mechanics. The predictions of Newton's Mechanics refer only to the term 'force' as it had been defined within Newton's Mechanics.

5. As soon as T has been included in SM, SM generates the relationships between T and other elements, and makes predictions that include T. These predictions can then be compared with external reality. 6. If the predictions of SM related to T prove to be acceptable, then SM is considered useful in understanding T. If the predictions are unacceptable, then SM is inadequate in understanding T. In neither case, SM can be considered correct or incorrect. 7. Any prediction connected to T has to be associated with the SM which produced it.

Example: Gravity is a supposition of Newton's theory. In his theory gravity is a property of the mass of a physical body. In Einstein's theory (another symbolic model), gravity is a property of space and mass. Both theories give good predictions in known specific situations.

8. As the predictions of SM related to T are proved acceptable, SM is considered suitable in understanding T and thus, the predictions of SM including T can be associated with the term knowledge.

Knowledge based on an acceptable SM is the purpose of any positive science.

We'll see now an extremely complex example. We have intentionally chosen a term which practically has no definition in GCL (the definitions is unclear) and has no associated direct data and facts from the external reality. The term chosen is 'alien' (ET).

To study within a positive science a term like ET seems impossible; we will see that this is not so. According to the logical schematic presented, we need a symbolic model (a positive science), which in our example is MDT itself.

Generation of a definition of the term ET in MDT means that we accept that ETs have a brain and more, their brain works based on the same principle as the human brain. This can be difficult to accept, but independent of the used SM (MDT or another), the situation is the same: SM generates the definition of ET, whatever SM is, and whatever the definition of ET in GCL might be. We'll try to explain ET in MDT.

Let's activate MDT with ET included. MDT considers that the basic functions of the brain are the construction of image models [I] and symbolic models [S].

Let's define a human brain [H] with the parameters I=1, S=1. It is very likely that ET will not have the same parameters. Let's suppose a model of ET with the parameters ET(1,10)(the same capacity to build image models as humans, but ten times capacity to build symbolic models). This is just a possible example. In a complete analysis we need to use a collection of values (I,S).

After having choosen a pair (I,S), we start operating MDT with ET included. We can ask a first question, e.g. how can the interaction between a human H(1,1) and an ET(1,10) look like? Which are the tendencies of the ET? Do they want to communicate, do they want to be friends or enemies, etc.

MDT can't answer these questions yet. We need to calibrate the model. Calibration is done asking questions with known answers.

For instance, a dog might be associated to D(0.1,0) (10% of the capacity to operate image models compared to a human and zero capacity to operate symbolic models). We have the tendency to communicate with dogs and do not have an exagerated tendency to exterminate them. On the other hand, we have the tendency to exterminate mosquitoes which have an extremely low I value and S=0.

We can go on with calibration studying the interaction among humans. For instance, the Asiatic have clearly a higher I value than the Europeans, and the Europeans have higher S.

Once the system is somehow calibrated, extrapolation to given situations is possible. Based on prediction, we can evaluate which are the limits for I and S for a friendly or unfriendly interaction.

Let's not forget that no prediction of the model can be verified yet in interaction with external reality. However, the fact that we have a collection of predictions, brings us a huge advantage. If some facts from external reality could be in the range of predictions of the model, we will be already prepared to interpret them in specific conditions. Thus, some facts can be explained if ET had a certain formula. Anyways, we already have a collection of probable behaviours, which represents a big advantage, when some facts from external reality could be explained by the existence of ET.

We can go even further. Depending on the formula chosen for ET, models of civilisation could be built for each type of ET. Again, the model can be calibration based on known types of human society, including those existing in the past, and extrapolating to various formulas for ET.

Please remember that even if ET existed in external reality, and even if MDT gave exact predictions, it does not result from here in any way, that ET have brains which function as MDT considers.

A positive science only declares the model and gives predictions. If, based on verifying the predictions, we get confidence in the model, then the model will be used in other similar situations, as useful. Never and with no positive science do we expect that it will show us "the truth" or it will offer guarantees or certainties. A positive science, as we have shown above, makes predictions. If the model makes good predictions, we will use it again, and that's all.

Let's see another possible direct practical application associated to the above example. We could build models to tell us what could happen with human society if S=2. Or, what would happen if the dispersion in S increases too much. This means to find out, for instance, if a danger exists for civilization if 50% of humans have S=0.5 and 50% have S=1.5. Perspectives look fascinating!

ETA 22: Direct demonstration of the function to create image models

The basic assumption of MDT is that the brain builds and operates models automatically (this is a hardware function). An exercise is described below which demonstrates directly this basic assumption.

The absolute majority of beings (human or animal) have two eyes. They generate two plane images but what we see is a single tri-dimensional image (photographic-type image model) in accordance with MDT. Moreover, if we have a single plane image (we look with one eye) the brain will continue to build the tri-dimensional model.

But we have got a problem: with a single plane image we have not enough information to build a tri-dimensional image. However we have a "compensation": the brain is an extremely powerful system. It will use any kind of supplementary information to build first a tri-dimensional image and then, the tri-dimensional model. In the following, we will describe an exercise for beginners to demonstrate this.

We need to watch TV with a single eye in a room with no additional light source. The glass surface of the screen has to be absolutely invisible (there should be absolutely no reflection of light on it). We have to sit in front of a normal screen at least at 3 meters distance (we should not be able to see the pixels which build up the image). The screen should show a familiar picture, from common external reality, in normal perspective, and the image has to change slowly.

If, under these circumstances, we watch the screen with one eye, after some training, we will see a tri-dimensional image. This experiment proves directly that the basic function of the brain is to make image models.

The generation of tri-dimensional models by the brain starting from a plane image is known for a long time. This appeared at the same time with the expansion of art painting trade, many hundreds of years ago. Thus, a painter used to paint first the foreground, and later the background. A good painter had the whole tri-dimensional model in his head, and the background connected perfectly with the foreground, even if the background was painted a lot later. In some paintings, the background or some components of the painting do not match perfectly (a poor painter) and this could be noticed by art experts looking at the painting with one eye.

Rembrandt painted scenes with groups of people. However, some people in the group could be "closer" or "farther" from the viewer. When such a compact group is watched with a single eye, one can notice that the painter had painted them correctly (the persons farther out are slightly smaller). Our brain can notice tiny differences, because it reconstructs the 3-D model.

By the way: to build a 3D model based on a single plane image is an operation which requires an immense capacity of processing of information. In spite of its huge power, the brain has problems with the capacity of processing such a huge amount of information. As in principle there is not enough information for such an operation, the brain has to guess one or several probable models, which have to be verified. From my direct experience, in order to guess a 3D model from a plane image ones has to be in a very good physical and psychical shape.

ETA 23: Some basic parameters of the brain for measuring performance

Based on the fundamental theory, I have listed several basic functional facilities of the brain, exclusively as an introduction to the problem evaluation.

1. The capacity to build and operate image models (arts, many games, paranormal qualities...) 2. The capacity to build and operate symbolic models (positive science, technologies...) 3. The capacity to build and operate purely symbolic models (Quantum Mechanics...) 4. The capacity to integrate an image into a pre-existing image model 5. The capacity to translate an image model to GCL (description of an image model) 6. The capacity to translate a symbolic model to GCL (the symbolic model is associated to a certain case, translated to an image model and described in words) 7. The capacity to translate an image model to a symbolic model (general abilities in science) 8. The capacity to translate a symbolic model to an image model 9. The capacity to integrate symbolic information into an image model 10. The capacity to build concept-type image models from a family of image models 11. The capacity to build a concept-type symbolic model from a family of symbolic models. 12. The capacity to integrate symbolic information into a symbolic model 13. The speed to build/operate image models 14. The speed to build/operate symbolic models 15. The speed to build long range image models 16. The speed to build long range symbolic models 17. The speed/capacity to update preexisting models 18. The capacity/speed to build shielding models 19. The capacity to build a new model in front of a new external reality 20. The speed of finding a pre-existing model suitable to a new external reality 21. The speed of activation and deactivation by MZM of a preexisting model in front of a changing external reality. This implies both finding the suitable model and initializing it to the given external reality 22. The capacity to operate in time-sharing several models in front of a complex external reality

This list can continue, as the brain is extremely complex.

For instance: Endurance parameters (e.g. the quality of the technological implementation), dynamical parameters (e.g. the speed and stability of the operations, how fast one can switch from one operation to another in transient and stationary mode).

In the general theory, the brain appears as having two basic facilities: to build and operate ZM models associated to external reality, and to act on the external reality, based on a ZAM model. The facility of action on the external reality has a number of parameters, starting from building ZAM suitable to the external reality and ending with the capacity of activation of the action models.

This possible list of parameters is far from characterizing completely the brain.

From this we can see the naivete and ridicule of the present so-called intelligence tests. These tests are ridiculous, because there is no fundamental theory, which could at least define and correlate the used terms.

My theory says that there are facilities associated to image and to symbolic models (there are arts and sciences, watches are analog or digital, on computer screens we have icons and text etc.) We also have facilities associated with obtaining information from the external reality and facilities associated with modifying the external reality. A minimum observation of the external reality suggests four independent groups of IQ tests: action/knowledge on image/symbolic models. As this is not the case, the present IQ tests are naive and ridiculous, not only from the point of view of MDT.

In the following we will give a structure of fundamental IQ tests based on MDT: 1. The capacity to build M image models 2. The capacity to build YM image models (concept models) 3. The capacity to assimilate image YM 4. The capacity to build symbolic YM 5. The capacity to assimilate symbolic YM 6. The capacity to assimilate image ZM 7. The capacity to build image ZM 8. The capacity to assimilate symbolic ZM 9. The capacity to build symbolic ZM 10. The capacity to assimilate symbolic ZAM 11. The capacity to build symbolic ZAM 12. The capacity to assimilate image ZAM 13. The capacity to build image ZAM 14. The capacity to activate symbolic ZAM 15. The capacity to activate image ZAM 16. The capacity to build image AZM 17. The capacity to activate image AZM

Example: For a person who has to be a public relations representative for a business, the qualities which will count, on first place, are the capacity to assimilate symbolic and/or image models and to act based on them. He has to have a reduced tendency to build own models, in order to be fit to the requirements of the position. A person who will work in scientific research has to have capabilities to create new symbolic models.

Among these capabilities, interdependence should exist. We can suppose that persons who have the tendency to build models will have difficulties to assimilate external models. Their tendency will be to modify any external model in a personal manner. At the same time a person with capabilities of assimilation of external models, will have diffculties in building own new models, and will not try to modify the assimilated models, even if they are not suitable to the external reality anymore.

Other parameters associated to the brain are connected with the stability of these capabilities, on long/ short term, and in normal or extreme conditions. These parameters will charactrize the reliability of these capabilities in special conditions.

Based on this theory and further work, a collection of human types will be possibly established as a list of numerical paramters. As soon as a person is considered to belong to a specific type, he/she will know that his/her chances to socially integrate are big, if he/she will pursue the domain where he/she has adequate qualities.

The above examples are only as an illustration of the capabilities of MDT in this field. A fundamental theory as MDT cannot be used directly to solve specific problems. It creates a basis and a referential system, where specific problems associated with some sections of the extrenal reality can be solved.

ETA 24: Animals

Bees

A basic characteristic of a bee is its flight beyond its visual limit. It can fly some hundreds of meters from the beehive, while it can identify objects only withing a few meters distance. In consequence, the bee must navigate. Navigation means, in principle, the existence of a map, compass and of a dynamical system of finding the actual position on the map. If we can make only suppositions about the compass and the dynamical positioning system, as to the map, we find ourselves in the action zone of the theory. A map is an image model. The brain builds simplified models (maps) of the external reality, marking the position of the beehive and the position of the bee in flight and updating that all the time.

When a young bee comes out of the beehive, it will start flying around it, in wider and wider circles, but only on clear days. The explanation based on the theory is that, in this flight, the bee is calibrating its navigation system. This means that it calculates its position relative to the beehive and compares the prediction with external reality, as given by direct view. When the instruments of navigation are calibrated, it can fly beyond the limit of direct visibility, and return successfully based on the predictions of its map model.

Migratory birds

In the case of migratory birds, we have again a navigation problem. This time the flight is done at thousands of kilometers distance. It is clear that the migratory birds should have a map added to the navigation instruments. The birds should have in memory a successful story-type model (map) of the wanted route. The bird will compare the wanted position (given by the story-type model) with the real position. The real position could be found e.g. by following the magnetic field of the Earth, by observing the position of cosmic bodies (Sun, Moon, and stars). It is clear that any supplementary information is welcome and added to the story-type model, to sustain a successful operation. The navigation story-type model has been built based on a previous successful flight. A bird, which has not this model, could record it, if it is a member of a flock in which at least one bird has this model.

However, if a bird, which has not yet the navigation map, has technical problems in flight, it could be lost. Examples are known of migratory birds, which having technical flight-problems, were eventually taken into care by people. After healing, they did not want to leave anymore. The theory explains this by the fact that without a map and their position on the map, they don't know where to go. However, if they see a flock in flight, they might follow that flock.

There is a situation reported by the media, when a whole flock lost its navigation map and remained stranded. In this situation, a plane resembling a bird was used to guide the flock.

Cats

Cats can communicate to some extent with humans. Another characteristic is that a cat hardly adapts to an environment after getting used to another. A house cat is jumpy at sounds to which it should be familiar. When a cat is disturbed, it is very likely that PSM was activated.

At first sight, cats have a brain with a reduced capacity to build new models. At the same time, due to a weak instinct of defending its territory (some cats accept mice around them), one can suppose that the cat's model of the territory is very primitive. The most probable situation is that a cat can build new models only when very young. After some time it looses the capacity to build long-range models and uses mainly short-range models, guided by primitive long-range models and many solutions based on the action of PSM.

In fact, all predators having few enemies have the tendency to use more short- range efficient models, than long-range models. Thus, intelligence, which is an indicator of the capacity to build and operate long-range models, is not stimulated in predators. Animal intelligence is stimulated by the presence and interaction with humans, and also by an aggresive environment.

It is important to note that in spite of the fact that the lack of external danger is not a stimulus to develop the functions of the brain, the potential of the predators brain is relatively high. This is why, even if predators do not look too intelligent, they can surprise us in critical situations.

Dogs

Dogs seem to build very precise models of the external reality, including sensing the mood of the master. Their relatively high capacity to build models, gives them a possibility to communicate based on these models, including with humans.

Let's analize now a situation, as it was reportd in the newpapers. A shepherd was walking with his dog in the forest. A mother bear with cubs attacked him. The bear attacked the shepherd, but the dog attacked the cubs. The bear left the shepherd, to save its cubs.

The theory can explain this behaviour in several ways. A first possibility is that the master is integrated in the dog's PSM. The dog builds a defence model of the master, which, at the simulation of the bear attack, fails to find a successful solution. Simulating the attack of the cubs, the prediction appears that the bear will save the cubs and forget about the shepherd. This explanation is clearly a sign of intelligence (long-range model). It is a bit too complex for a dog (it is even surprising even for humans).

Another variant is that after the model to attack the bear failed, the dog attacked the cubs because it was less dangerous. This means that the master was not in the PSM.

Another variant exists in which the dog has participated previously in an attack of several dogs against a mother-bear, and in that attack, it saw that the bear runs with the cubs when the cubs are attacked. This variant again does not consider the shepherd. This seems to be the most probable explanation.

Another variant exists in which the shepherd is not considered, and the dog attacks anything weaker than itself.

Let's continue the analysis of dogs. It is known that dogs are very faithful to their master. This suggests that they can introduce the master into their PSM. However, the fact that some dogs can be faithful to several masters (successively) suggests that they can rewrite the PSM. This is really unusual.

The fact that dogs introduce the master in the PSM is clearly demonstrated by the observation that some dogs die to save their master (they are not afraid of death). According to the theory, this can happen only if the masters are on the same priority level with their own being.

There are fights with dogs, when dogs fight to death. It is interesting to see if the motivation can or can't be given by a protection model of the master, or by an instinct, which does not take the master into account.

The elephant

The brain of the elephant could be bigger than the human brain. From this follows that its organization is primitive. A way to explain this is the reduced capacity of the elephant brain to build concept models. If this is true, he uses a huge capacity of the brain to build pure image models. The term "elephant memory" can be associated with this feature. Thus, if it built concept model, the elephant should be able to identify only limited landmarks of the places it passes by. Using pure image models, it memorizes each tree and each branch. This is a totally inefficient mode of brain functioning.

Monkeys