There is an increasing agreement in the cognitive sciences community that our sensations are closely related to our actions. Our actions impact our sensations from the environment and the knowledge we have of it. Cognition is grounded in sensori-motor coordination.
In the perspective of implementing such a performance in artificial systems, there is a need for a model of sensori-motor coordination.
We propose here such a model as based on the generation of meaningful information by a system submitted to a constraint . Systems and agents have constraints to satisfy which are related to their nature (stay alive for an organism, avoid obstacle for a robot, …). We propose here to use an existing meaning generation process where a system submitted to a constraint generates a meaningful information (a meaning) when it receives an information that has a connection with the constraint . The generated meaning is precisely the connection existing between the received information and the constraint of the system. The generated meaning is used to trigger an action that will satisfy the constraint. The generated meaning links the system to its environment. A Meaning Generator System (MGS) has been introduced as a building block for higher level systems (agents). The MGS allows to link sensation and action through the satisfaction of the constraint of the system/agent. We use the MGS in a model which is based on constraint satisfaction for sensori-motor coordination in agents, be they organic or artificial. The meaning is generated by and for the agent that hosts the MGS. Such approach makes possible an addressing of the concept of autonomy through the intrinsic or artificial nature of the constraint to be satisfied (organisms with intrinsic constraints/autonomy, artificial systems with artificial constraints/autonomy). The systemic nature of the MGS also allows to position the groundings of the generated meaning as being in or out of the MGS, and correspondingly identify the constructivist and objectivist components of the generated meaning.
The approach presented here makes available a sensori-motor coordination by meaning generation through constraint satisfaction with groundings of the generated meaning.