The authors develop a mathematical framework for cognitive systems—both artificial and natural—that aligns with enactivism, a philosophical position in cognitive science. They identify five core enactivist tenets and build a model that avoids attributing contentful symbolic representations to agents, instead treating the nervous system, body, and environment as an inseparable whole. The central concept is a sensorimotor system, a special case of a transition system. They introduce the notion of sufficiency as a foundational concept, proving a uniqueness theorem about minimal sufficient refinements, which correspond to an optimal attunement of an organism to its environment. This framework aims to make enactivist ideas accessible to computer scientists, AI researchers, and roboticists, while providing philosophers a mathematical tool for clarifying debates.
This work identifies five core principles of enactivist cognitive science from the literature and builds a mathematical framework for modeling cognitive systems—both artificial and natural—that adheres to those principles. The framework avoids attributing contentful symbolic representations to agents and treats brain, body, and environment as an inseparable whole. The central concept is a sensorimotor system, a type of transition system. The authors introduce the notion of sufficiency as a foundational concept, prove a uniqueness theorem about minimal sufficient refinements (which correspond to optimal attunement of an organism to its environment), and relate sufficiency to existing concepts like sufficient history information spaces. The work aims to make enactivist ideas accessible to computer scientists, AI researchers, and psychologists, while providing philosophers a mathematical tool.