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Abstract: Dominant models of cognition have been
shaped by mechanistic and reductionist assumptions that conceptualize mental
processes as linear, decomposable, and computationally analogous systems. While
these models have provided analytical clarity and methodological rigor, they
encounter limitations when applied to environments characterized by complexity,
uncertainty, and continuous interaction.
This article introduces a post-linear
framework of cognition that reconceptualizes cognitive processes as dynamic,
relational, and temporally integrated. Rather than treating cognition as a
sequence of discrete operations, the framework emphasizes the interaction of
multiple cognitive potentials operating simultaneously across time and context.
The analysis examines the limitations of
mechanistic cognition, including its reliance on linearity, modular
decomposition, and machine-based metaphors. It then develops an alternative
perspective grounded in four principles: superposition, entanglement,
relational embedding, and developmental trajectory.
The article argues that cognition should be understood as a probabilistic and emergent field rather than a deterministic processing system. This shift enables a more comprehensive understanding of how cognition operates under real-world conditions and provides a foundation for analyzing cognitive vulnerability, adaptation, and resilience. DOI: http://dx.doi.org/10.51505/ijaemr.2026.11228 |
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