Dynamic Interactions in Artificial Environments: Causal and Non-Causal Aspects for the Emergence of Meaning
Argyris Arnellos, Thomas Spyrou, John Darzentas
Initially, the analysis and development of adaptive artificial systems has been based in metaphors taken from philosophical schools as well as the disciplines of biology and cognitive science. So far, the dominant approaches exhibit many advantages in specific domains of application but there all have a certain drawback, which is their inability to produce an artificial system which will be able to internally ground its representations so as to use them to produce newer, more developed ones. The respective frameworks are studied in terms of this inability and it is concluded that the problem is traced in the purely causal treatment, function and creation of the notion of representation, wherever it is used. In the case of purely dynamic systems, where the representations seem not to be very useful, it is proposed that the incorporation of a special non-causal kind of representations would give a framework which seems promising in realizing real adaptation. The relevant architecture is analyzed and discussed mainly in terms of its functionality and its contribution to the integration of pragmatic meaning aspects in an artificial system’s interaction.