Morphological Computing as Logic Underlying Cognition in Human, Animal, and Intelligent Machine
This is a foundational but incremental theoretical framework for researchers in cognitive science, AI, and philosophy, aiming to unify logic across natural and artificial agents.
The paper tackles the problem of understanding the origins of logic in cognition by proposing that it emerges from scale-invariant, self-organizing dynamics across physical, chemical, and biological levels, applicable to humans, animals, and machines, but it does not provide concrete numerical results.
This work examines the interconnections between logic, epistemology, and sciences within the Naturalist tradition. It presents a scheme that connects logic, mathematics, physics, chemistry, biology, and cognition, emphasizing scale-invariant, self-organizing dynamics across organizational tiers of nature. The inherent logic of agency exists in natural processes at various levels, under information exchanges. It applies to humans, animals, and artifactual agents. The common human-centric, natural language-based logic is an example of complex logic evolved by living organisms that already appears in the simplest form at the level of basal cognition of unicellular organisms. Thus, cognitive logic stems from the evolution of physical, chemical, and biological logic. In a computing nature framework with a self-organizing agency, innovative computational frameworks grounded in morphological/physical/natural computation can be used to explain the genesis of human-centered logic through the steps of naturalized logical processes at lower levels of organization. The Extended Evolutionary Synthesis of living agents is essential for understanding the emergence of human-level logic and the relationship between logic and information processing/computational epistemology. We conclude that more research is needed to elucidate the details of the mechanisms linking natural phenomena with the logic of agency in nature.