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| Format: | Recurso digital |
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Zenodo
2026
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| Teme: | |
| Online dostop: | https://doi.org/10.5281/zenodo.19664618 |
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- <p><strong>Abstract</strong></p> <p>This work introduces a theoretical framework for understanding intelligences as entities evolving within a dynamically reconfigurable space of possibilities. Departing from classical approaches where constraints are treated as fixed limitations acting on a predefined space, this manuscript proposes a fundamental inversion: constraints are modeled as dynamic operators that co-determine the structure of the space itself.</p> <p>The central contribution is the formulation of a dynamic topology of intelligences, in which the space of configurations X(t) is continuously reshaped by the evolution of constraints C(t). As a result, key structural properties—such as connectivity, accessibility, and admissible trajectories—are no longer invariant, but become time-dependent and history-dependent. This leads to a framework where space, constraints, and trajectories co-evolve and cannot be analyzed independently.</p> <p>The manuscript develops this perspective through three core dimensions: (i) the evolution of accessible and forbidden regions, (ii) the transformation and interaction of constraints, and (iii) the global effects of these transformations, including instabilities, emergent structures, and intrinsic limits of control. It is shown that phenomena such as unpredictability, irreversibility, and partial controllability are not contingent limitations, but necessary consequences of this co-evolutionary structure.</p> <p>A central result is the Principle of Dynamic Topology of Intelligences, which states that any intelligence evolves within a space whose topology is continuously transformed by the non-stationary and non-commutative dynamics of constraints. This principle redefines intelligence not as a system operating in a fixed environment, but as a trajectory embedded in a structurally evolving space.</p> <p>Beyond its formal contributions, this framework provides a unified foundation for analyzing complex systems across physical, computational, and artificial domains. It also opens new research directions, particularly toward the study of meta-trajectories—trajectories of transformations of the space itself—and the integration of multi-physical constraint regimes.</p> <p>Overall, this work establishes a shift from static representations of possibility spaces to a fully dynamic, constraint-driven ontology of intelligences.</p>