Arnellos, Argyris5; Bruni, Luis Emilio1; El-Hani, Charbel Niño6; Collier, John8
1 Sektion København, The Faculty of Engineering and Science (ENG), Aalborg University, VBN2 Aalborg University Copenhagen, The Faculty of Humanities, Aalborg University, VBN3 Department of Architecture, Design and Media Technology, The Faculty of Engineering and Science (ENG), Aalborg University, VBN4 The Faculty of Engineering and Science (TECH), Aalborg University, VBN5 IAS-Research Centre for Life, Mind, and Society - Department of Logic and Philosophy of Science, University of the Basque Country6 Institute of Biology, Federal University of Bahia, Bahia7 University of KwaZulu-Natal8 University of KwaZulu-Natal
Integrating the Tools to Model Information and Normativity in Autonomous Biological Agents
We argue that living systems process information such that functionality emerges in them on a continuous basis. We then provide a framework that can explain and model the normativity of biological functionality. In addition we offer an explanation of the anticipatory nature of functionality within our overall approach. We adopt a Peircean approach to Biosemiotics, and a dynamical approach to Digital-Analog relations and to the interplay between different levels of functionality in autonomous systems, taking an integrative approach. We then apply the underlying biosemiotic logic to a particular biological system, giving a model of the B-Cell Receptor signaling system, in order to demonstrate how biosemiotic concepts can be used to build an account of biological information and functionality. Next we show how this framework can be used to explain and model more complex aspects of biological normativity, for example, how cross-talk between different signaling pathways can be avoided. Overall, we describe an integrated theoretical framework for the emergence of normative functions and, consequently, for the way information is transduced across several interconnected organizational levels in an autonomous system, and we demonstrate how this can be applied in real biological phenomena. Our aim is to open the way towards realistic tools for the modeling of information and normativity in autonomous biological agents.