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README.md
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CosmosMesh MVP # CosmosMesh Privacy-Preserving Federated Mission Planning (CatOpt 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. This repository holds an MVP scaffold for privacy-preserving federated mission planning across heterogeneous deep-space assets (rovers, drones, habitat modules, orbiting satellites).
Core ideas Key idea
- Local optimization problems (variables, objectives, constraints) with explicit data contracts and versioning. - Map CosmosMesh primitives to a lightweight CatOpt-style representation to enable plug-and-play adapters and cross-domain experimentation without heavy dependencies.
- 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) Core MVP outline
- Implement a 2–3 asset testbed (rover, drone, habitat) with a simple quadratic objective and an ADMM-lite solver. - Objects = LocalProblems (per-asset planning tasks)
- Define data contracts: Telemetry, Forecast, Command, Event, and Trade-like signals with versioned schemas. - Morphisms = SharedVariables / DualVariables (data channels with versioned contracts)
- Delta-sync protocol: deterministic reconciliation for intermittent links with per-message metadata and audit logs. - Functors = Adapters translating device-specific models into canonical CosmosMesh problems
- Identity & security baseline: DIDs or short-lived certs, secure aggregation by default. - Lightweight transport (TLS-based) and a tiny ADMM-lite solver per asset
- Adapters and simulation: two starter adapters and a space-scenario simulator to evaluate convergence and resilience. - Graph-of-Contracts registry for schemas and per-message metadata to support audits and replay protection
- 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 What’s included in this patch
- Build: python3 -m build - Added a minimal CatOpt bridge module: src/cosmosmesh_privacy_preserving_federated/catopt_bridge.py
- Test: ./test.sh - Package initializer: src/cosmosmesh_privacy_preserving_federated/__init__.py
- 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). - 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
- Publishing readiness How to run tests
- If you want to signal readiness for public publishing, create an empty file named READY_TO_PUBLISH in the repo root. The publish workflow will detect this file as a sign that the repo is prepared for packaging and release. This repository's pyproject.toml already hooks the README into the package metadata, so the marketing description will accompany the published artifact. - Ensure Python 3.8+ environment
- Notes - Run: bash test.sh
- 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. - The test suite includes a basic sanity check for the CatOpt bridge encoding.
Changelog-style summary Next steps (high level)
- Added CatOptBridge (lightweight CosmosMesh -> CatOpt representation) in the MVP scaffold. - Wire two starter adapters (rover planner and habitat life-support) into the bridge
- Exposed CatOptBridge via the MVP package API for quick experimentation. - Implement a small ADMM-lite solver per asset and a toy end-to-end round trip
- Expanded README to reflect MVP architecture, extension paths, and evaluation plan. - Add delta-sync protocol scaffolding and an auditable reconciliation log
Public artifacts This work aligns with the roadmap described in AGENTS.md and is designed to be extended incrementally.
- 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
CatOpt MVP Bridge (Overview)
- The MVP includes a lightweight CatOpt bridge that maps CosmosMesh primitives to a CatOpt-like representation (Objects/Morphisms/Functors).
- Core components:
- src/cosmosmesh_privacy_preserving_federated/catopt_bridge.py: translator skeleton for LocalProblem, SharedVariables, DualVariables, PlanDelta
- src/cosmosmesh_privacy_preserving_federated/dsl_sketch.py: lightweight DSL scaffolding for MVP primitives
- src/cosmosmesh_privacy_preserving_federated/contract_registry.py: minimal contract registry
- Reference adapters (toy scaffolds) added under src/cosmosmesh_privacy_preserving_federated_/reference_adapter.py to illustrate how rover and habitat domain adapters would interface with the bridge
- A tiny Graph-of-Contracts registry supports versioning for LocalProblem/SharedVariables/DualVariables/PlanDelta contracts
- Next steps (optional): TLS transport adapters, secure aggregation, and governance ledger integration
# 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.

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src/cosmosmesh_privacy_preserving_federated/__init__.py
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"""CosmosMesh MVP packages """CosmosMesh privacy-preserving federated MVP package initializer."""
Lightweight scaffolding for a CatOpt-style bridge and two starter adapters from .catopt_bridge import CatOptBridge, LocalProblem, SharedVariable, DualVariable
to bootstrap CosmosMesh privacy-preserving federated mission planning.
"""
from .catopt_bridge import ( __all__ = ["CatOptBridge", "LocalProblem", "SharedVariable", "DualVariable"]
LocalProblem,
SharedVariables,
DualVariables,
PlanDelta,
CatOptBridge,
)
__all__ = [
"LocalProblem",
"SharedVariables",
"DualVariables",
"PlanDelta",
"CatOptBridge",
]

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src/cosmosmesh_privacy_preserving_federated/catopt_bridge.py
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from __future__ import annotations """
Minimal CatOpt bridge for CosmosMesh MVP.
from dataclasses import dataclass, asdict This module provides a tiny, self-contained mapping layer between
from typing import Any, Dict, List, Optional CosmosMesh primitives and a canonical CatOpt-inspired representation.
It is intentionally lightweight and safe to extend in subsequent MVP
iterations.
"""
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Any, Dict, List
import time
@dataclass @dataclass
class LocalProblem: class LocalProblem:
id: str """Represents an asset-local optimization problem."""
problem_id: str
objective: str objective: str
variables: Dict[str, Any] variables: List[str]
constraints: List[str] constraints: List[str] = field(default_factory=list)
version: int = 1 version: int = 1
def to_object(self) -> Dict[str, Any]:
return {
"ObjectType": "LocalProblem",
"id": self.problem_id,
"version": self.version,
"objective": self.objective,
"variables": self.variables,
"constraints": self.constraints,
}
@dataclass @dataclass
class SharedVariables: class SharedVariable:
"""Represents a data channel (primal variable sharing)."""
name: str name: str
value: Any value: Any
timestamp: float version: int = 1
def to_morphism(self) -> Dict[str, Any]:
return {
"MorphismType": "SharedVariable",
"name": self.name,
"version": self.version,
"value": self.value,
}
@dataclass @dataclass
class DualVariables: class DualVariable:
"""Represents the dual variable channel (Lagrange multipliers)."""
name: str name: str
value: Any value: float
version: int = 1
def to_morphism(self) -> Dict[str, Any]:
@dataclass return {
class PlanDelta: "MorphismType": "DualVariable",
delta_id: str "name": self.name,
changes: Dict[str, Any] "version": self.version,
timestamp: float "value": self.value,
}
class GraphOfContracts:
"""Simple in-memory registry for contract schemas and versions."""
def __init__(self) -> None:
self._contracts: Dict[str, Dict[str, Any]] = {}
def register(self, name: str, version: str, schema: Optional[Dict[str, Any]] = None) -> None:
self._contracts[name] = {"version": version, "schema": schema or {}}
def get(self, name: str) -> Optional[Dict[str, Any]]:
return self._contracts.get(name)
def all(self) -> Dict[str, Dict[str, Any]]:
return self._contracts
class CatOptBridge: class CatOptBridge:
"""Minimal CatOpt bridge that maps CosmosMesh primitives to a canonical CatOpt view. """Lightweight bridge mapping CosmosMesh concepts to a CatOpt-like layer."""
This is intentionally lightweight and serves as a scaffold for MVP wiring. # Registry of contracts/schema versions for adapters
""" _contract_registry: Dict[str, Dict[str, Any]] = {}
def __init__(self) -> None: @classmethod
self._registry = GraphOfContracts() def register_contract(cls, contract_name: str, contract_spec: Dict[str, Any]) -> None:
cls._contract_registry[contract_name] = {
# Contract registry helpers "spec": contract_spec,
def register_contract(self, name: str, version: str, schema: Optional[Dict[str, Any]] = None) -> None: "registered_at": int(time.time()),
self._registry.register(name, version, schema)
def get_contract(self, name: str) -> Optional[Dict[str, Any]]:
return self._registry.get(name)
def all_contracts(self) -> Dict[str, Dict[str, Any]]:
return self._registry.all()
# Translation primitives (annotation-friendly, minimal)
def to_catopt(self, lp: LocalProblem, sv: SharedVariables, dv: DualVariables) -> Dict[str, Any]:
"""Translate CosmosMesh primitives into a minimal CatOpt-like representation."""
catopt = {
"Objects": {
"LocalProblem": asdict(lp),
},
"Morphisms": {
"SharedVariables": asdict(sv),
"DualVariables": asdict(dv),
},
"Functors": {
# Placeholder for adapter bindings (empty by default)
},
} }
return catopt
def from_catopt(self, catopt: Dict[str, Any]) -> Dict[str, Any]: @classmethod
"""Minimal reverse-translation from CatOpt-like representation to a dictionary. def get_contract(cls, contract_name: str) -> Dict[str, Any] | None:
return cls._contract_registry.get(contract_name)
This is intentionally permissive for MVP; it merely returns the input structure @staticmethod
in a normalized dict form for downstream processing. def problem_to_object(problem: LocalProblem) -> Dict[str, Any]:
""" return problem.to_object()
return dict(catopt)
@staticmethod
def variables_to_morphisms(shared: List[SharedVariable], duals: List[DualVariable]) -> List[Dict[str, Any]]:
morphisms: List[Dict[str, Any]] = []
morphisms.extend([s.to_morphism() for s in shared])
morphisms.extend([d.to_morphism() for d in duals])
return morphisms
@staticmethod
def encode_message(kind: str, payload: Dict[str, Any], version: int = 1) -> Dict[str, Any]:
return {
"kind": kind,
"version": version,
"timestamp": int(time.time()),
"nonce": int(time.time() * 1000) & 0xFFFFFFFF,
"payload": payload,
}
# Convenience helpers for a minimal end-to-end round
@classmethod
def build_round_trip(cls, problem: LocalProblem,
shared: List[SharedVariable],
duals: List[DualVariable]) -> Dict[str, Any]:
obj = cls.problem_to_object(problem)
morphs = cls.variables_to_morphisms(shared, duals)
return cls.encode_message("RoundTrip", {"object": obj, "morphisms": morphs})
__all__ = [ __all__ = ["CatOptBridge", "LocalProblem", "SharedVariable", "DualVariable"]
"LocalProblem",
"SharedVariables",
"DualVariables",
"PlanDelta",
"GraphOfContracts",
"CatOptBridge",
]

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tests/test_catopt_bridge.py
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import pytest import math
from cosmosmesh_privacy_preserving_federated_.catopt_bridge import CatOptBridge from cosmosmesh_privacy_preserving_federated.catopt_bridge import (
from cosmosmesh_privacy_preserving_federated_.contract_registry import REGISTRY CatOptBridge,
LocalProblem,
SharedVariable,
DualVariable,
)
def test_registry_and_translation(): def test_basic_roundtrip_encoding():
bridge = CatOptBridge() # Build a tiny LocalProblem and signals
# Register a simple contract and verify registry exposure lp = LocalProblem(
bridge.register_contract("LocalProblem", "0.1.0", {"schema": {"type": "object"}}) problem_id="lp-task-01",
assert REGISTRY.get("LocalProblem")["version"] == "0.1.0" objective="minimize_energy",
variables=["x1", "x2"],
constraints=["x1>=0", "x2>=0", "x1+x2<=10"],
version=1,
)
# Translate a minimal local problem description sv1 = SharedVariable(name="sigma", value=0.5, version=1)
local_problem = { dv1 = DualVariable(name="lambda", value=1.25, version=1)
"name": "TestProblem",
"variables": [{"name": "x", "domain": "R"}], round_msg = CatOptBridge.build_round_trip(lp, [sv1], [dv1])
"objective": {"type": "quadratic"},
} # Basic invariants about the payload
translated = bridge.translate_local_problem(local_problem) assert round_msg["kind"] == "RoundTrip"
assert translated["type"] == "LocalProblem" payload = round_msg["payload"]
assert translated["name"] == "TestProblem" assert payload["object"]["id"] == lp.problem_id
assert any(m.get("name") == sv1.name for m in payload["morphisms"])
assert any(m.get("name") == dv1.name for m in payload["morphisms"])