The Evolution of Intelligence from Active Matter to Complex Intelligent Systems via Agent-Based Autopoiesis

Intelligence is a central topic in computing and philosophy, yet its origins and biological roots remain poorly understood.The framework proposed in this paper approaches intelligence as the complexification of agency across multiple levels of organization-from active matter to symbolic and social systems.Agents gradually acquire the capacity to detect differences, regulate themselves, and sustain identity within dynamic environments.Grounded in autopoiesis, cognition is reframed as a recursive, embodied process sustaining life through self-construction.Intelligence evolves as a problem-solving capacity of increasing organizational complexity: from physical self-organization to collective and reflexive capabilities.The model integrates systems theory, cybernetics, enactivism, and computational approaches into a unified info-computational perspective.