THE INTERTWINED NATURE OF SIMPLICITY AND COMPLEXITY: A NEW PARADIGM FOR UNDERSTANDING COMPLEX ADAPTIVE / AUTONOMOUS / LIVING SELF-IMPROVING SMART SYSTEMS

Research in the field of autonomous systems focuses on developing machines, robots, and systems capable of autonomous learning, perceiving their environment, and interacting with it like a living being. For autonomous systems, flexibility in the face of limited resources and radical uncertainty is critical, and system failures are unacceptable. The key research question: How is the balance between complexity and simplicity achieved in cognitive systems? Resource economy leads to criticality - a self-organizing balance between simplicity/parsimony and complexity. In terms of the evolutionary self-improvement of (natural) smart systems, the 'System 0/1/2/3' architecture has been substantiated. The limit generalizations paradigm offers a holistic approach to the complexity-simplicity trade-off.