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README.md
CosmosMesh MVP
CosmosMesh is a privacy-preserving federated mission-planning scaffold designed for deep-space constellations. It targets offline-first operation with intermittent connectivity, enabling heterogeneous assets (rovers, aerial drones, habitat modules, orbiting satellites) to coordinate planning and resource usage without centralization.
Core ideas
- Local optimization problems (variables, objectives, constraints) with explicit data contracts and versioning.
- Federated optimization core: an ADMM-lite solver that exchanges only summarized signals to preserve locality.
- Lightweight global assembly: fleet-wide constraints (energy, time windows, safety) applied without re-deriving the entire global model.
- Delta-sync and offline resilience: deterministic reconciliation on reconnects with audit trails.
- Privacy-by-design: secure aggregation by default, optional local DP budgets, and role-based access controls.
- Identity & security: DID-based identities, short-lived certificates, and tamper-evident logging.
- Adapters & simulation: reference adapters for rover/habitat/space assets, plus a scenario simulator for offline validation.
- Open API and governance: schema registry for data contracts and a governance ledger to anchor decisions.
MVP plan (8–12 weeks)
- Implement a 2–3 asset testbed (rover, drone, habitat) with a simple quadratic objective and an ADMM-lite solver.
- Define data contracts: Telemetry, Forecast, Command, Event, and Trade-like signals with versioned schemas.
- Delta-sync protocol: deterministic reconciliation for intermittent links with per-message metadata and audit logs.
- Identity & security baseline: DIDs or short-lived certs, secure aggregation by default.
- Adapters and simulation: two starter adapters and a space-scenario simulator to evaluate convergence and resilience.
- Global constraints layer: light fleet-wide constraints that bind local problems during aggregation.
- MVP milestones: Phase 0 protocol/specs + 2 adapters; Phase 1 offline validation; Phase 2 cross-domain demo; Phase 3 HIL.
- Metrics: convergence speed, plan-optimality gap, delta-sync latency, and privacy budgets.
Getting started
- Build: python3 -m build
- Test: ./test.sh
- Explore: src/cosmosmesh_privacy_preserving_federated_/ and src/cosmosmesh_privacy_preserving_federated_/catopt_bridge.py for the MVP scaffolding and the CatOpt bridge (lightweight interoperability layer).
Notes
- This repo focuses on a safe, minimal surface suitable for rapid iteration. Extend with adapters for rovers, habitats, and orbital assets, plus a delta-sync protocol and a light global-assembly layer in follow-on work.
Changelog-style summary
- Added CatOptBridge (lightweight CosmosMesh -> CatOpt representation) in the MVP scaffold.
- Exposed CatOptBridge via the MVP package API for quick experimentation.
- Expanded README to reflect MVP architecture, extension paths, and evaluation plan.
Public artifacts
- README.md (detailed MVP plan and extension guidelines)
- Python modules in src/cosmosmesh_privacy_preserving_federated_ and src/cosmosmesh_privacy_preserving_federated_/catopt_bridge.py
- Tests in tests/ (smoke test for basic arithmetic)
- READY_TO_PUBLISH flag to be created when ready for publication
CosmosMesh MVP: Privacy-Preserving Federated Mission Planning
This repository contains a minimal MVP scaffold for privacy-preserving, offline-first, multi-agent mission planning in deep-space fleets. It includes a tiny ADMM-lite solver and contract primitives, plus a CatOpt-style interoperability bridge for cross-domain experimentation.
Key artifacts:
- LocalProblem / SharedVariables / DualVariables / PlanDelta / PrivacyBudget / AuditLog contracts (in src/cosmosmesh_privacy_preserving_federated/contracts.py)
- ADMMLiteSolver (in src/cosmosmesh_privacy_preserving_federated/admm_lite.py)
- CatOpt bridge (in src/cosmosmesh_privacy_preserving_federated/catopt_bridge.py): minimal translator between CosmosMesh primitives and CatOpt-like representations
This MVP is designed to be extended in small, well-scoped steps. See AGENTS.md for contribution and testing guidelines.