Changelog

All notable changes to MOSAIC will be documented here.

[1.0.0] - 2026-02-24

Added

  • Operator Abstraction: Unified agent-level interface for RL, LLM, VLM, and Human decision-makers

  • IPC Worker Protocol: stdin/stdout JSON protocol making any worker interchangeable

  • Two Evaluation Modes: Manual Mode (lock-step side-by-side) and Script Mode (automated batch)

  • 8 Integrated Workers: CleanRL, XuanCe, Ray RLlib, BALROG, MOSAIC LLM, Chess LLM, Human Worker, Random Worker

  • 26 Environment Families: Gymnasium, Atari, MiniGrid, BabyAI, ViZDoom, NetHack, Crafter, Procgen, BabaIsAI, Jumanji, PyBullet Drones, PettingZoo, MOSAIC MultiGrid, INI MultiGrid, Melting Pot, Overcooked, SMAC, SMACv2, RWARE, MuJoCo

  • Heterogeneous Decision-Maker: Mix RL, LLM, Human, and Random agents in the same multi-agent environment

  • Homogeneous Decision-Maker: Deploy teams of identical paradigm (all-RL, all-LLM, all-Human)

  • Multi-Keyboard Support: Linux evdev-based per-keyboard routing for multi-human play

  • Deterministic Cross-Paradigm Evaluation: Shared seed schedules for reproducible comparison

  • Script Mode Configs: Declarative Python scripts for automated batch evaluation

  • Curriculum Training: CleanRL DoorKey progression with environment wrappers

  • XuanCe Solo Training Configs: Soccer and Basketball (blue/green teams)

  • Visual-First GUI: PyQt6 interface for experiment configuration, rendering, and telemetry

  • Resource Management: GPU allocation, queue limits, health monitoring

  • Per-Agent Policy Binding: PolicyMappingService for routing agents to workers

  • Runtime Logging: JSONL telemetry per step and episode

  • Sphinx Documentation: Full docs with video demos, architecture diagrams, and API reference