This work proposes a framework that models cognitive processes using temporally localized goals and structures, suggesting new insights into machine intelligence.
This work proposes a constraint-observed framework for modeling cognitive dynamics, in which goals and meaning structures are treated as temporally localized outputs rather than persistent causal primitives. The paper introduces the concept of multi-anchor temporary closure and explores implications for stability, constraint interaction, and machine intelligence.
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G M Sturm (2026) studied this question.
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