Modelling dynamics of cognitive agents by higher-order potentialities

Abstract

In the development of disciplines addressing dynamics, such as Mathematics and Physics, a major role was played by the assumption that processes can be modelled by introducing certain state properties (also called potentialities) that anticipate in which respect a next state will be different. The current paper is a first exploration of this perspective to analyse and model dynamics. Potentiality-based modelling subsumes quantitative, numerical modelling approaches, such as Dynamical Systems Theory (DST), and qualitative or symbolic modelling approaches to dynamics, such as BDI-modelling, and is applicable to model dynamics in a wide variety of (cognitive and noncognitive) disciplines. Thus, the modelling of dynamics of cognitive agents can be fully integrated with the modelling of other phenomena in Nature.