ResearchResearch paperRobotics & Embodied AI · Agents & Tool Use · Reinforcement Learning1 source · Oct 19, 2026

Topological Sheaves of Irreducibility: A Theoretical Framework for Multi-Agent Task Obstructions

We introduce Topological Sheaves of Irreducibility (TSI), a sheaf-theoretic framework separating task-level compatibility obstructions from system capability.

Key points

  • Multi-agent systems can differ under identical agents and communication budgets when they support different forms of joint interaction.
  • A task is represented by an interaction complex $K$ and a capacity sheaf $\mathcal{F}$; nonzero $H^n(K;\mathcal{F})$ defines a structural signature, while registered interventions test capability.
  • For cocycle data, cochain realization is solvable exactly when the represented cohomology class vanishes.
  • On a degree-2 tetrahedral-boundary task over 531,441 inputs, the same-2-skeleton system retains all four three-agent primitives yet matches the pairwise-only optimum throughout the registered separation window, whereas adding the class-filling four-agent primitive makes both tasks exact.

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