Possibility does not evolve in a vacuum. Every actualisation occurs within a horizon structured by constraints, and these constraints are often treated as fixed. Yet relational ontology reveals a subtle but profound truth: constraints themselves evolve in response to the actualisations they govern.
This post examines how relational horizons dynamically modify their own constraints, producing an iterative, self-shaping evolution of possibility.
Constraints as Active Participants
Traditionally, constraints are assumed to be static rules: the laws of physics, grammatical norms, or mathematical axioms. From a relational perspective:
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Constraints are properties of horizons, not independent forces.
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They are activated by actualisations, shaping what can occur next.
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Critically, constraints themselves adapt or transform when patterns of actualisation consistently reshape the horizon.
In this sense, constraints are both limiting and generative, guiding potential while being modified by the very potentials they enable.
Iterative Actualisation
Consider a semiotic system:
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A language imposes grammatical constraints, enabling intelligible sentences.
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New idioms or forms emerge, stretching or reshaping the rules themselves.
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The constraint system evolves, producing a new horizon of potential expressions.
Similarly, in physics:
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Conservation laws and symmetries describe patterns of relational actualisation.
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Novel experimental setups or boundary conditions reveal limitations or extensions of these constraints.
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The laws themselves are understood as stabilised regularities within a changing horizon, not immutable decrees.
Iterative actualisation ensures that possibility is never static; each actualisation reverberates back, subtly altering the landscape of what can occur next.
Nested Horizons and Constraint Feedback
Constraints evolve not in isolation, but within nested horizons:
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Local horizons: govern immediate actualisations (e.g., a particle system, a conversation, a cultural practice).
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Meta-horizons: oversee broader patterns (e.g., theoretical frameworks, institutional norms, universal principles).
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Interactions between levels produce feedback loops: changes at one level reshape the possibilities at another.
The horizon is thus self-referential, dynamically adjusting its constraints in response to actualisations occurring within and across levels.
Implications for Evolution of Possibility
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Dynamic adaptability: Horizons are not fixed; they learn and evolve as actualisations accumulate.
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Generative tension: Constraints both limit and enable, producing emergent novelty.
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Recursive complexity without chaos: The interplay of evolving constraints produces structure without requiring pre-existing order.
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Cross-domain continuity: The same principle operates in semiotic, physical, and mathematical systems — constraints shape actualisation, and actualisation shapes constraints.
Possibility is therefore co-constitutive: actualisations and constraints are mutually generative, each reshaping the other over time.
Examples Across Domains
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Language evolution: Grammar evolves as new forms, idioms, and usages feedback into the system, modifying what counts as well-formed.
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Physics: Boundary conditions, experimental interventions, and new symmetries extend or reinterpret laws, showing that constraints are contextually emergent.
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Mathematics: Formal systems evolve as new axioms, constructions, and proofs reshape the scope of what can be expressed or demonstrated.
In each case, the evolution of possibility is iterative, relational, and self-modifying.
Conclusion
Constraints are not static walls but dynamic participants in the evolution of possibility. They shape, guide, and limit what can actualise — while simultaneously being reshaped by the patterns of actualisation they govern.
The horizon itself learns, adapts, and co-evolves. Actualisation and constraint are inseparable, forming a continuous feedback loop that drives the evolution of possibility.
The next post, “Horizons Folding Horizons”, will explore nested and overlapping horizons, showing how relational systems at different levels interact, constrain, and co-generate possibilities — a deeper dive into the recursive architecture of potential itself.
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