The fantastic power of reasoning !

Human reasoning (alias syllogism): the foundation for a true artificial intelligence

I – « Simple » reasoning

Reasoning with binary facts

Let’s take this simple knowledge: « every living being is mortal » and you’ll see what we can deduce:

It is a knowledge, a truth that unites two facts: « living being » and « mortal ». Whether I understand these two facts or not this association allows me to automatically generate new knowledge that will serve to those who understand. Therefore the computer can manipulate information for its users. These facts can only be true or false unlike the other two types of facts that can take several states. Numerical facts – such as age, for example – and multivalued facts – like color – can take an infinite number of states.
I know that a fact can not be both true and false. If it is true, it can not be wrong … And vice versa. So nothing can be both living and non-living, mortal and immortal. Otherwise there is a contradiction. In this case, three hypotheses: either my reasoning is wrong (if I’m tired for example), or my knowledge is false (for example I use the truth « when it is noon then it’s dark »), or a fact I’m using to reason is false (I reason on « it’s dark » while it is known to be noon). In the latter case I have to determine what fact is wrong (it is night? Or it is noon?).
I call « rule » the knowledge « every living being is mortal », and in order to well separate the two facts that compose it and facilitate subsequent reasoning, I’ll write: « IF it is a living being THEN it is mortal ».
With this rule I can produce other knowledge. For example, since a tree is a living being then it is mortal.
I can also deduce that if I want to prove that something is mortal, it will suffice to establish that it is alive. To the question « Is it mortal? » I can answer « yes if it’s alive ».
By cons I do not deduce if it is not alive then it is immortal: a corpse, stone, water, fire, the planets are not alive and yet we know they are mortal.
Very interesting : from this rule – like any rule – I automatically infer another rule called « contraposition » : IF it is immortal THEN it is not a living being. I therefore conclude that God, for example, is not a living being … With the contraposition we double the power of reasoning.
The contraposition allows to deduce this : if I’m asked « such a thing is immortal? » I can respond by asking « is this a living? « (Backward chaining). Because if the answer is « yes », I reply: No, this thing is not immortal. If the answer is « no », I would say I do not know.

You see, it’s amazing what can be inferred from … nothing! This is what can do most animals (without telling us because they do not speak). Here’s how, using reasoning, living beings are able to survive in a hostile world …

2. Reasoning with multi-valued facts

Let’s consider a slightly more complicated knowledge: « IF it is sunny AND the sky is cloudless THEN the sky is blue« .

Here, « the sky is blue » is a fact different from the previous facts: it may take more than the usual two states TRUE or FALSE. It is « multi-valued ». Indeed, the sky can also be pink, gray, black, red, white. In each of these cases, I conclude that it can not be blue. A color can not have two states at once, it is the logic itself …
Thanks to the contraposition, which applies to all rules regardless of their complexity, I deduce another rule: « IF the sky is not blue THEN it is not sunny OR the sky is not cloudless « .
This leads me to infer, among others, this new rule: « If the sky is not blue AND it is sunny THEN the sky is cloudy« .
And I deduce another rule: « IF the sky is not blue AND the sky is cloudless THEN it is not sunny« .
So the more a rule contains facts, the more it allows to deduce new rules. The more a knowledge is complex the more it is possible to deduce new knowledge. Great, is not it?

Is your head hurt ?

With knowledge like below, imagine what can be deduced :

IF the collision occurs at an intersection
AND one of two vehicles is traveling on a roundabout
AND this roundabout has a tag « Yield »
AND it is you who drive in this roundabout
THEN the other vehicle comes into the roundabout
AND you have priority
AND your responsibility = 0

3. Reasoning with numerical facts

Let’s consider this sentence: « IF you are 18 THEN you have the right to vote« . This is correct but in the case of numeric facts it is not complete. Indeed, the contraposition is false: IF you do not have the right to vote THEN you are not 18. We must therefore review again the rule for it to be fair in all cases: « IF you are 18 years or older THEN you have the right to vote« .

When a fact is digital it can take an infinite number of values. Our brains have little talent for mathematics and infinite prefer the logic. They will arrange to have no calculation to be done and will therefore create this truth: If your age is GREATER THAN or EQUAL TO 18 years THEN you have the right to vote. Under course, there is only another alternative : the case where it is less than 18 No need to make a calculation, a comparison is sufficient and comparison, we can do from our childhood. Although the age of an individual ranges between 0 and 120 years, making countless cases, my brain simplifes the maximum and limits the number of opportunities to … two : <18 and> = 18. That’s to say a binary fact !

Fianlly we have : « IF you are at least 18 years old THEN you have the right to vote« .

II – « Complex » reasoning : production of knowledge

Direct reasoning

Now let’s combine simple truths:

1st rule: IF it is a living thing THEN it is mortal
2nd rule: IF it is a man THEN hit is a living thing
3rd rule: IF its name = « Socrates » THEN it is a man

Each of these rules separately produces the 10 deductions previously defined. But, by linking them to each other (« intellegere »!) According to the virtues proper to the syllogism, I produce new knowledge. Example: if his name is Socrates, I automatically deduce 3 new knowledge: he is a man, he is a living being and he is mortal. Just as I deduce from the contradiction that if it is not mortal, then it is not a living being, it is not a man and it is not Socrates.

If one asks me: « What I have in front of me, is it deadly? « I know that I have three ways to find the solution. By asking first « it is a living being? « . If I am told I do not know, I ask: « Is it a man? « . If I am told I do not know, I ask, « Is he called Socrates? « . If, yes, I answer yes, I link the deductions and I can answer: yes, it’s deadly. By the same token, I provided my interlocutor with three new truths that he did not know since he answered I do not know twice.

What I have just described here is what I call a reasoning mechanism. It’s very easy to program. This is what is found in Pandora and that university researchers scornfully call the zero-order logic.

2. Ad absurdum Reasoning

Ad absurdum reasoning is a form of reasoning used when one cannot find a direct reasoning. It uses the contradiction. For example, with the 3 rules above, I am asked to establish whether God is a man or not, knowing that he is immortal. None of the 3 rules tells me that God is a man or not. « To see », I then assume that he is a man. With the help of the first two rules, I come to the conclusion that, in this case, it would be mortal. As I know God is immortal. So he can’t be a man. QED …

3. Demonstrations of automated reasoning

Want to see software driven by reasoning? Click here, you will see a list of small expert demonstration systems that you can test (sorry, in French !). To better understand the validity of a reasoning in real life, take the payroll : « Gestion du personnel –> mini-paye » and click on the arrow. You then have the choice between two attitudes: or fill in the input screen that appears, or not. Then you validate. If you have not completely completed the input screen, some information will be missed and the software will switch to Conversational to get them.

Attention, it’s an old software! It runs in Francs, with 169h / month the legal duration of work, a SMIC of 5 756,14 F and the legislation of the time. If you indicate a salary lower than this SMIC, it will give an error and you will not arrive at the end. In any case, the software will show you the deductions (in white and underlined) as it produces them, until the end: « net salary to pay ».

One of the many deficiencies of computing: the obligation for the developer to learn the knowledge of experts to put in programs

Publié par Jean-Philippe de Lespinay

1. A program = an expertise

Any program is the automation of a human expertise. Payroll is the automation of an accounting expertise, device drivers are automation of engineering expertises, input screen are automation of ergonomist expertise crossed with programmer expertise, electronic mail is automation of users expertise, databases management system are the automation of computer expertises, etc.. And if you want to develop a program without having an expert close at hand, you will obliged to create the expertise what will make you an expert …

Of course, expertise contained in a program is usually complex, rare and essential. This is because it is complex that its users, however daily, fail to assimilate. This is because it is rare that it must be saved in a program in order not to lose it when the expert will disappear. This is because it is daily essential for users that they need a program that helps and saves them time.

We saw in my previous post « Algorithmic, sad consequence of the wrong postulate that computer is stupid » an algorithmic program is the identification of all possible ways of reasoning to solve a given class of problems. For collecting these arguments, the computer scientist is forced to simulate the operation of the expertise in his head, therefore to learn it and understand it. This is an almost superhuman exercise because, remember, the users themselves, yet familiar with the subject, do not succeed.

When he considers that he has fully assimilated the expertise, the programmer begins a new unhuman task: to represent all the paths that can be taken in a kind of equation : the algorithmic. This work will fill dozens or hundreds of pages depending on the volume of the expertise and the result must always work. We understand that writing a program is not a long calm river …

2. Human procedural memory and expertises

The computer can store an infinite number of pages without forgetting anything but man not at all. However this does not prevent him to achieve the same results and we would do well to learn from this ! He uses his simplifying intelligence and his « procedural » memory. This memory , possessed by all living things, stores repeated experiences and tells instantly what to do in front of known cases. It is the memory of the expert ( knowing that we are all experts in a multitude of things). The man pushed this feature much further than his colleagues animals. The evolution helped him by increasing its cranial capacity at a surprisingly fast speed in his last few hundred thousand years. In fact since he stands up which helped lay the weight of his heavy head on the rest of the body minimizing efforts, rather than a door-to-front overhang head like all animals moving horizontal.

Procedural memory consists of a multitude of micro-expertises that say what to do based on a given situation. The oldest and most common in a human are the language, the interpretation of expressions, psychology, driving, etc. Here are examples of human micro-made expertises in various specialized areas:

IF number of salary hours to pay> legal number of monthly hours
AND POSITION OF EMPLOYEE is not « executive »
THEN there are overtime to pay

IF you are in the area of Toulon-Camarat
AND wind force after breezes <4
AND wind direction after breeze > 2 and <6
WHEN the wind is northerly

IF the pain I feel does not mention a heart problem
AND it does not increase when I breathe
AND I do not have fever
AND I cough
THEN I have a pleurisy

IF I have an accident at an intersection
AND the other vehicle is on a roundabout
AND this roundabout has a sign « Give way »
AND I do not still circulating on the roundabout
THEN I am driving into the roundabout
AND I do not have priority
AND my share of responsibility in the accident = 1

In computer science and artificial intelligence, they are called « rules ». You collect all the rules of an expertise in a database which is called « rules base » or « knowledge base » . It is on them that the expert reasons unconsciously to execute an equivalent of the program, as for example we all reason unconsciously to understand this text, or to talk or to drive.

3 .Expertise = artificial intelligence

It turns out that, contrary to what many believe, each reasoning is a very simple mechanical. A mechanical as unconscious as a rule but with a power much greater since guide our actions every second and it is what keeps us alive. This is the « syllogism » described by Aristotle there 2400 years. You can discover its extraordinary power in this post. Since this is a simple and clear mechanical, it is programmable ! And this program knows how to exploit a rule base and reason on it like the expert. Even better than him because it never forgets anything, never makes a mistake and answered without the slightest delay.

By copying the thought process of the expert and provided that we have a rule base, we obtain a program without the intervention of a programmer, without algorithmic or computer language. We have a program written in clear under form of rules and easy to modify. The computer works out the rules without understanding the concepts it manipulates and yet it provides you the right answers that it does not understand either. But, you, you understand ! Like any program.

Remains to solve the ultimate challenge : to allow the computer to automatically find these rules it does not understand … Otherwise we will always have to use a developer to query the expert, and he will always have to assimilate knowledge for divide it into rules. Remember the topic of this post : « Another major flaw of computing: the obligation for the developer to learn the knowledge of experts to put in the programs ». It implies that it would be possible to program without understanding anything about the knowledge of the expert, so without even understanding the expert. God ! How is this possible ?

4. « La Maïeutique », a method to produce AI without any computer skills

That is here where my invention « La Maieutique » gains its value. It is a method, therefore also mechanical. It allows the computer to question experts and automatically extract their expertise in the form of rules. If the computer does not understand what it does, the expert, he can see the rules that are synthesized and can check if it has « understood » . If it does not understand the expert corrects.

With La Maieutique the computer is a force of proposal and the expert is the inspector of finished work. The machine proposes, the woman – sorry, the man! – disposes (for once). This really is the most comfortable way of working .

This means that with La Maieutique the expert defines the program and the computer writes it without understanding.

Not nice this invention?

You will guess that I am not loved by computer scientists ! 😉

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