Behavioral Control of Cognitive Agents Using Database Semantics and Minimalist Grammars

Knowledge representation and processing, learning and adjusting knowledge models, communication and interaction as well as problem solving are important skills of cognitive agents. But, in order to share the learned knowledge with other communication participants, the agent must pay attention to maintaining its own functionality when interacting with the physical environment. To comply with this requirement, the meaning of perceptions and the consequences of actions must be understood. This suggests that even the non-verbal exchange of information is based on the foundations of semiotics. In this work, we show that we can model non-verbal interactions with the same linguistic means as verbal communication. We demonstrate this by solving the bidirectional translation problem of symbolic sequences into semantics through the use of minimalist grammars. To verify this approach, we turn back to the well-known example of a cognitive mouse agent living in a maze world and model the interaction and behavioral control using database semantics in a fully deterministic setting. Finally, we propose a unifying perspective for non-verbal interaction and verbal communication as well as justify its relevance for Cognitive Infocommunications.