Eduardo Sánchez-Soto

Manuel Hernández, Eduardo Sánchez-Soto

Multi-agent coordination faces a fundamental divide between continuous Euclidean consensus, which fails under non-integrable constraints, and discrete symbolic logic, which collapses under open-world assumptions. This report presents a unified geometric and categorical framework bridging these paradigms. Agent states are modeled on homogeneous manifolds (Lie groups, Grassmannians) with consensus achieved via Riemannian center-of-mass flows. Clifford-algebraic representations (rotors, motors) enable singularity-free SE(3) pose synchronization. Network interactions are formalized as cellular sheaves, where heterogeneous stalks connected by linear restriction maps replace uniform weights; the sheaf Laplacian drives diffusion toward globally consistent sections. The Cartan connection encodes logical holonomy directly into restriction maps. Asynchronous nonlinear sheaf diffusion guarantees linear convergence to Dirichlet energy minimizers under bounded delays. Sheaf-Theoretic Planning (STP) models time as a Grothendieck topos, using intuitionistic logic and abductive repair for resilient temporal reasoning. Applications include discourse sheaves for opinion dynamics and knowledge sheaves for graph embedding. This synthesis establishes geometric consensus as a universal foundation for resilient multi-agent systems across physical, epistemic, and temporal domains.

Manuel Hernández, Eduardo Sánchez-Soto

The coordination of heterogeneous autonomous agents in dynamic, adversarial environments requires simultaneous satisfaction of geometric constraints, logical consistency, temporal reasoning, and strategic optimization. Existing sheaf- and topos-theoretic frameworks provide powerful tools for geometric consensus, knowledge alignment, and causal planning, but lack explicit models for value, reward, and strategic choice. This report presents a unified categorical framework that integrates event calculus, SCEL-like ensemble formation, and game-theoretic reward structures into a single Grothendieck topos of time-space histories. We introduce the notion of a \emph{game sheaf} whose stalks contain utility functions and policy distributions, and restriction maps encode both parallel transport and best-response dynamics. We prove that Nash equilibria correspond to global sections of a derived best-response correspondence sheaf, while cohomological obstructions classify failures of strategic consistency. A detailed case study of an immunological ``bastion defense'' scenario -- heterogeneous agents forming attack/defense ensembles under resource constraints -- demonstrates the framework's expressiveness. This synthesis provides a rigorous foundation for verifiable, autonomic, and economically rational multi-agent systems.

Manuel Hernández, Eduardo Sánchez-Soto

The challenge of engineering autonomous agents capable of navigating the stochastic and adversarial nature of the physical world has historically resided at the intersection of symbolic logic and control theory. Traditional multi-agent system (MAS) frameworks have relied heavily on monolithic logical models -- primarily variations of the event calculus and situation calculus -- to represent action, change, and temporal persistence. While these classical systems provide robust solutions to the frame problem through mechanisms like circumscription and successor state axioms, they are inherently limited by a closed-world assumption that fails in the face of unobserved agent interventions, plan interruptions, and divergent belief-reality states. The paradigm of Sheaf-Theoretic Planning (STP) emerges as a transformative alternative, grounding the problem of multi-agent coordination under the mathematical structures of topos theory and sheaf semantics. This report provides an exhaustive analysis, justification, and extension of the STP framework, exploring its categorical foundations, implementation feasibility, and role in the future of resilient autonomous systems.