Software Metadata
Name: ARGOS — Adaptive Recursive Gradient Optimization System
Version: 1.0.1
Release Date: 2025
License: MIT
Repository: https://github.com//argos-hotel-optimization
Programming Language: Python 3.9+
Primary Dependencies: NumPy, Pandas, Matplotlib
Supported Platforms: Linux, macOS, Windows
Continuous Integration: GitHub Actions (optional)
Documentation: Included in docs/ and notebooks in notebooks/
Primary Purpose:
Stable hierarchical optimization under strict lexicographic priorities, combining
Lexicographic Constraint Optimization (LCO) with Componentwise Approximated Gradient (CAG).
Research Domains:
- Operations Research
- Optimization & Control
- Reinforcement Learning (CMDP-style)
- Hospitality Management Systems
- Multi-agent & Multi-unit resource allocation
Key Features:
- Lexicographically safe updates (Tier-1 invariants always preserved)
- Componentwise selective gradient filtering (CAG)
- Integrated LCO + CAG update engine (ARGOS Core)
- Single-unit and multi-unit hotel environment simulators
- Ablation tools (Newton-only, CAG-only, full ARGOS)
- Reproducible experiments via CLI and Colab notebooks
Intended Users:
Researchers, operations analysts, optimization practitioners, and academic collaborators evaluating lexicographically constrained decision systems.
How to Cite:
Valamontes, A. (2025). ARGOS: Adaptive Recursive Gradient Optimization System (Preprint).
Full Changelog: ARGOSv1...ARGOSv2