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Problem: In multi-asset edge ecosystems (robotics fleets, microgrids, mobility hubs), coordination requires composing many local optimization problems into a coherent global plan. Current solutions are fragmented across domains and vendor stacks, ham
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README.md

CatOpt-Graph MVP

Graph-Calculus-Driven Compositional Optimization Studio for Edge Meshes

Overview

  • CatOpt-Graph provides a minimal, pragmatic MVP for compositional optimization across edge meshes. It introduces a light-weight ontology (Objects, Morphisms, Functors) and a tiny ADMM-lite solver that demonstrates delta-sync/for reconnections while converging on a simple global constraint.

What you get in this MVP

  • Core ontology scaffolding: Object, Morphism, Functor, and a tiny versioned contract registry.
  • ADMM-lite solver: asynchronous, two-agent solver with bounded staleness and deterministic reconciliation on reconnects.
  • Adapters: rover and habitat stubs that map to a canonical representation.
  • Lightweight governance/contract conformance scaffolding.
  • Basic transport surface (mocked for MVP) and tests.

How to run

  • This project is Python-based. See test.sh for the test runner which also builds the package to validate packaging metadata.
  • After cloning, run: bash test.sh

Long-term vision (brief)

  • Protocol skeleton bridging to Open-EnergyMesh/runtime, a Graph-of-Contracts registry, API bindings for adapters, and a simulated HIL environment with Gazebo/ROS.

This README is a marketing and onboarding document for the MVP. The code is intentionally minimal but designed to be incrementally extended towards a working cross-domain orchestration platform.

Package metadata

  • The Python package name is catopt-graph-graph_calculus_driven_compo per the repository requirements.
  • See pyproject.toml for build configuration and packaging details.

License

  • This MVP is provided as-is for exploration and testing purposes.

Contributing

  • See AGENTS.md for architectural guidance and test commands. .