One of the fundamental frameworks views behavioral (or cognitive) products as a process within a dynamic system. The mechanism might be seen as a representation of many instances of centralized control in real time. Many real systems, however, exhibit autonomy by denying treated mechanisms in a static manner. Networks, which have the ability to show sophisticated relationships, provide us with an ideal means of satisfactorily characterizing using nonlinear dynamics.
For understanding this directed behavior as a call for the organism-environment system rather than simply the organism, I explored the biological autonomy and control of function according to their surrounded circumstances that the purported relationship to the environmental cycle. In a similar vein with the Ecology and Evolution Program, I will address the issues related to the identification of dynamic systems using an ecological perspective, that is, functional non-linearity. In particular, I will suggest how determining the basic principles of a collective structure could be the key to understanding complex processes which occur as part of real-time phenomena. A primary model will be derived to assess the advantages of this perspective via a basic methodology. This connection between perspective and technique will demonstrate certain aspects in an actual context while also explicitly including the framework of actual dynamic system identification.
Funding: IIASA - NRF Korea Postdoctoral Fellowship
Program: Evolution and Ecology Program
Dates: March 2017 - present
Last edited: 14 March 2017
Related research program
Postdoctoral research at IIASA
International Institute for Applied Systems Analysis (IIASA)
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