Information and Meaning

Christophe Menant (crmenant[at]free.fr)

Foundations of Information Science - April 2002 -

Abstract:
We propose here to clarify some of the relations existing between information and meaning by showing how a meaning can be generated in a system submitted to a constraint. We build up definitions for a meaningful information, a meaning generator system and the domain of efficiency of a meaning (to cover the cases of meaningful information transmission).
Basic notions of signal and information processing are used.

Content:
1) Introduction. Meaning versus information.
2) The nature of meaning. Meaningful information.
3) Meaning generator system.
4) Meaning transmission. Domain of efficiency of a meaning.
5) Conclusion and continuation.

Key Words:
Meaning, information, system, generation, constraint, transmission, efficiency

 

1) Introduction. Meaning versus information.

It is quite natural to say that information and meaning are different things.
When reading a newspaper, we skip items that do not interest us. We pay attention to information that has some meaning versus our subjects of interests.
A frog has a visual system able to see object the size of an insect or worm, providing it moves like one. Visual information of food that is not moving has no meaning for a frog.
The hive colony will extract information on food location from a bee dance because this food has meaning relatively to the survival of the hive.

And so on....

The impact of an information on a system depends upon the meaning it genarates in the system. The important thing for the system is the meaning generated by the incident information.

Now, what is the nature of this "meaning" ? How can it be generated by a system ?
We propose here after some answers to these questions.

 

2) The nature of meaning. Meaningful Information.

Pilosophers and scientists have analyzed questions relative to the meaning of words, sentences or signs. But not much has ben done regarding the nature of "meaning" as a concept, whatever the domain where you consider it.
Moreover, meaning has been so far studied essentially in relation with human. And this complicates the question because we do not know the nature of human.
So we feel it is necessary to start an analysis of "meaning" as generated by simple systems we understand well. A natural way for this is to analyse the generation of a meaningful information by some very simple living element.
Take for instance a paramecium living in water, and assume that the water becomes acid in the vicinity of the little animal. The paramecium will rapidly move away towards a less acid area. It seems quite obvious that the presence of acid in the vicinity of the paramecium has participated to the build up of some meaningful information in the paramecium. Meaningful information sounding like: "the environment is becoming incompatible with survival". And the paramecium to react correspondingly by moving away from the acid location.

Basically, three elements have participated to the creation of the meaningful information within the paramecium:
- The constraint of staying alive.
- The acid water becoming close.
- The incompatibility betweeen the satisfaction of the constraint and the acid water

This simple example of a paramecium building up "meaning" from the presence of acid water can be elaborated into a system representing the generation of a meaningful information.
Let's consider a system submitted to a constraint and let's assume that this system receives an external information that has some connection with the constraint. In order to satisfy the constraint, the system will generate a meaningful information that will initiate some action to satisfy the constraint.

Hereunder Figure 1 represents this modelization:

Such a modelization brings us to the definition on a meaningful information:

"A meaning is a meaningful information that is created by a system submitted to a constraint when it receives an external information that has a connection with the constraint. The meaning is formed of the connection existing between the incident information and the constraint of the system. The function of the meaningful information is to participate to the determination of an action that will be implemented in order to satisfy the constraint of the system".

(Properties of a meaningful information and more in I.1 at: http://crmenant.free.fr/uk/).

 

3) Meaning generator system.

The elements presented here above lead us to introduce more formally a meaningful information generation system (also called Meaning Generator System -MGS-) as made of:
- A system submitted to a constraint and able to receive an incident information.
- An information incident on the system.
- An information processing element, internal to the system and capable of identifying a connection between the received information and the constraint.

An MGS is represented in Fig 2 where a system submitted to a constraint S generates a meaningful (S) information.

(more on this in I.1 at: http://crmenant.free.fr/uk/ )

4) Meaning transmission. Domain of efficiency of a meaning

A meaningful (S) information created by a system S can exist for some action internal to S, but it can also be transmitted for usage by other systems (satisfaction of the constraint S can involve other systems).

Let's assume that the system (S) generates and sends out a meaningful (S) information, and that this information is received by another system (S') submitted to the constraint (S'). What will be the effect of the meaningful (S) information in the system (S') ?

In order to address this question, we need to define the "domain of efficiency (S) of a meaning" as being the domain where the meaningful (S) information is capable of participating to the determination of an action aimed at satisfying the constraint S.
We state that the meaningful (S) information is efficient (S) in the domain of efficiency (S).

These elements bring us to identify and analyse different cases where an information can be meaningful (S) or (S') and efficient (S) or (S'). Meaningfulness and efficieny will depend upon the location of the signal carrying the information versus the domains of efficiencies (S) or (S').

(more on this in I.3 at: http://crmenant.free.fr/uk/).

 

5) Conclusion and continuation

We have proposed here an approach to the notion of "meaning" by defining a meaningful information, a meaning generator system and the domain of efficiency of a meaning as relative to a system submitted to a constraint. A meaning is an information representing the connection between an incident information and the constraint of the system. This approach is to be continued by applying this systemic modelization to the different levels of complexity surrounding us (matter, life, mankind, machines).
A key point will be the identification of the constraints of the systems at each level of complexity.

(more on this in : http://crmenant.free.fr/uk/).