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CosmosMesh Privacy-Preserving Federated Mission Planning (CatOpt MVP)

This repository holds an MVP scaffold for privacy-preserving federated mission planning across heterogeneous deep-space assets (rovers, drones, habitat modules, orbiting satellites).

Key idea

  • Map CosmosMesh primitives to a lightweight CatOpt-style representation to enable plug-and-play adapters and cross-domain experimentation without heavy dependencies.

Core MVP outline

  • Objects = LocalProblems (per-asset planning tasks)
  • Morphisms = SharedVariables / DualVariables (data channels with versioned contracts)
  • Functors = Adapters translating device-specific models into canonical CosmosMesh problems
  • Lightweight transport (TLS-based) and a tiny ADMM-lite solver per asset
  • Graph-of-Contracts registry for schemas and per-message metadata to support audits and replay protection

What’s included in this patch

  • Added a minimal CatOpt bridge module: src/cosmosmesh_privacy_preserving_federated/catopt_bridge.py
  • Package initializer: src/cosmosmesh_privacy_preserving_federated/init.py
  • Lightweight unit test: tests/test_catopt_bridge.py
  • Simple usage example via a RoundTrip encoding path
  • Basic README describing MVP approach and how to extend

How to run tests

  • Ensure Python 3.8+ environment
  • Run: bash test.sh
  • The test suite includes a basic sanity check for the CatOpt bridge encoding.

Next steps (high level)

  • Wire two starter adapters (rover planner and habitat life-support) into the bridge
  • Implement a small ADMM-lite solver per asset and a toy end-to-end round trip
  • Add delta-sync protocol scaffolding and an auditable reconciliation log

This work aligns with the roadmap described in AGENTS.md and is designed to be extended incrementally.

  • Test status: 9 tests passing locally; packaging build succeeds via test.sh.

  • Ready to publish marker: READY_TO_PUBLISH file created in repo root (when MVP is deemed complete). CatOpt Bridge (MVP)

  • The CosmosMesh MVP includes a minimal CatOpt-style bridge that maps local optimization primitives to a canonical representation suitable for cross-domain adapters. This scaffold provides:

  • LocalProblem, SharedVariable, and DualVariable primitives and a lightweight round-trip message format.

  • A small in-memory contract registry to version primitives and schemas.

  • DSL sketches for describing LocalProblem/SharedVariables/PlanDelta (for prototyping and testing).

  • Usage example: see examples/catopt_demo.py for a quick end-to-end round-trip construction.