MAD-ATT II: Metabolic Attention Dynamics and the Emergence of Meaning

MAD-ATT II extends the previously proposed Metabolic Attention Dynamics (MAD-ATT) framework by introducing Meaning (M) and Skepticism as regulatory components within cognitive systems. In the original MAD-ATT model, attention was described as a metabolic process governed by interacting variables such as attention pressure (P), attention volume (V), and cognitive temperature (T). While this framework explained the dynamics of attentional redistribution, it did not fully address how signals become significant enough to generate attention pressure. The present work introduces Meaning as a tension field emerging from discrepancies between incoming signals and the internal state of a cognitive system. Rather than representing semantic content, Meaning is defined as an operational variable describing the structural deviation between expectation and observation. Within this framework, Meaning generates gradients that attract attention, guiding the flow of cognitive resources through the internal state space of the system. The paper further introduces Skepticism as a regulatory mechanism responsible for evaluating and stabilizing meaning gradients before they influence decisions and actions. Together, Meaning and Skepticism extend the MAD-ATT architecture into a metabolic cognitive cycle consisting of perception, meaning attribution, attentional redistribution, skeptical evaluation, decision formation, and action. The model also proposes that cognition operates through rhythmic cycles governed by a temporal constant regulating transitions between phases of interpretation and action. Different cognitive systems may exhibit distinct structural configurations that shape how tension flows through the system and how cognitive trajectories evolve over time. The metabolic framework is substrate-independent and may be applied both to the analysis of biological cognition and to the design of artificial cognitive systems. The paper concludes by outlining the concept of metabolic cognitive agents capable of maintaining internally regulated cycles of perception, interpretation, evaluation, and action. This work contributes to the theoretical foundations of cognitive dynamics, attention regulation, and adaptive cognitive architectures.