1.     Les formalismes de représentation de connaissances

 

Une manière courante de représenter des connaissances externes à un ordinateur ou à un être humain est sous forme de langage écrit. Par exemple, certains faits et relations représentés en français (écrit)  sont :

omar est grand //expression d’un fait simple grand est une proprité de omar.

Amine  aime son fils./ expression d’une relation

Amine  a appris à utiliser la récursivité pour manipuler des listes chaînées dans plusieurs langages de programmation.// plus complexe relation entre amine et concept abstrait (langage de programmation)

Les formalismes de représentation de connaissances

We do not know how knowledge is represented in the human brain,

but we can define some characteristics that will be important in representing problem-solving knowledge. Clearly, we will have to represent

facts, such as "an Alfa-Romeo is a car" or "Peter is a man." Furthermore, we must be able to represent relationships between these facts,

such as "Peter owns an AHa-Romeo." In reality, relationships can be

very complex, such as the management structure of a large organization or the structure of a huge organic molecule. Facts and relationships are obviously important, but they have limited value in themselves. It is the sort of knowledge we find in the data division of a COBOL program. It is not capable of solving problems. To solve problems we need knowledge that acts upon the facts and relationships and creates new ones. Such knowledge is equivalent to the procedure division of a COBOL program.

The procedural knowledge of a FORTRAN or COBOL program can be

represented in a variety of constructs.

 

Langage natural

 

Une manière courante de représenter des connaissances externes à un ordinateur ou à un être humain est sous forme de langage écrit. Par exemple, certains faits et relations représentés en français (écrit)  sont :

omar est grand //expression d’un fait simple grand est une proprité de omar.

Amine  aime son fils./ expression d’une relation

Amine  a appris à utiliser la récursivité pour manipuler des listes chaînées dans plusieurs langages de programmation.// plus complexe relation entre amine et concept abstrait (langage de programmation)

 

Autres formalisme

„ Triplets <objet, attribut, valeur>

„ Règles

„ Réseaux sémantiques

„ Frames

„ Logique

Types de logiques

Langages

Logique propositionnelle Faits vrai/faux/inconnu

Logique des prédicats Faits, objets, relations vrai/faux/ inconnu

Logique temporelle Faits, objets, relations, temps vrai/faux/inconnu

Théorie des probabilités Faits Degré de croyance 0 .. 1

Logique floue Degrés de vérité Degré de croyance 0 .. 1

 

2.     Knowledge Representation in Natural Language

Humans usually use natural language (English, Spanish, Chinese, etc.) to represent

knowledge, so why not use that to represent knowledge in our AI systems?

Advantages of Natural Language

1. It is extremely expressive – we can express virtually everything in natural language

(real world situations, pictures, symbols, ideas, emotions, reasoning, …).

2. Most humans use it most of the time as their knowledge representation of choice

(how many text books are not written in natural language?).

Disadvantages

1. Both the syntax and semantics are very complex and not fully understood.

2. There is little uniformity in the structure of sentences.

3. It is often ambiguous – in fact, it is usually ambiguous

3.     Databases as a Knowledge Representation

Traditional database systems are clearly very powerful, but for AI systems they are rather limited. The important issues are:

Advantages

1. Databases are well suited to efficiently representing and processing large amounts

of data (and derivation from a database is virtually independent of its size).

2. We can build on traditional database systems to process more complex and more

powerful representational devices (e.g. frames).

Disadvantages

1. Only simple aspects of the problem domain can be accommodated.

2. We can represent entities, and relationships between entities, but not much more.

3. Reasoning is very simple – basically the only reasoning possible is simple lookup,

and we usually need more sophisticated processing than that.

 

4.     Triplets

Sert à représenter un fait : un énoncé vrai ou faux.

 


آخر تعديل: الجمعة، 24 مارس 2023، 4:06 PM