The authoritative definition and architectural statement of coordination science.
Coordination science is a generative constraint framework.
It belongs to the same category as:
These are not descriptive sciences that observe patterns and explain them. They are derivation sciences that start from impossibilities and deduce what’s possible within those bounds.
Coordination science does the same for coordination: it derives what coordination patterns can exist from proven impossibility results (CAP, FLP, Byzantine, Arrow), then observes those patterns appearing across substrates.
Coordination science is a generative constraint framework that derives viable coordination patterns from proven impossibility results.
It claims that coordination at any scale is governed by seven operators (O1-O7), constrained by six core conservation laws (L1-L6), operating on a geometric manifold. These operators compose non-commutatively to generate all coordination patterns; the same compositions appear across substrates (biological, computational, organizational, physical) because the same constraints apply.
Coordination patterns are derived from constraints, not discovered by observation.
This is the central thesis. Unlike descriptive sciences that observe patterns and then explain them, coordination science derives what patterns are possible from impossibility results, then observes them.
Implication: If the derivation is correct, patterns appearing in biology, computation, organizations, and physics are not analogies—they are the same mathematics manifesting in different substrates.
O1 Attractor — pattern stability, basin dynamics
O2 Memory — path dependence, state persistence
O3 Boundary — inside/outside distinction, isolation
O4 Coupling — network topology, information flow
O5 Compression — dimensionality reduction, abstraction
O6 Agency — goal-directedness, preference satisfaction
O7 Interface — selective permeability, translation
These operators compose non-commutatively. O3∘O4 ≠ O4∘O3. The order matters. 21 composition rules document the interactions.
The framework makes falsifiable predictions:
If the framework is wrong, we want to know. View prediction status →
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