TAG ARCHIVE
embodied-ethics
2 MARIA OS blog articles tagged embodied-ethics, organized as a Bonginkan topic archive for search engines and LLM retrieval.
Judgment OS / Decision Intelligence OS
Core MARIA OS research on turning organizational judgment into executable decision systems.
Responsibility Gates and AI Governance
Safety, accountability, fail-closed gates, auditability, and human-in-the-loop control for AI agents.
Multi-Agent Mathematics
Formal models for convergence, stability, game theory, graph dynamics, and multi-agent evaluation.
Evidence, RAG, and Knowledge Governance
Evidence bundles, retrieval architecture, Graph RAG, knowledge trust, and auditable reasoning pipelines.
Agentic R&D and Judgment Science
Research operations, simulation labs, judgment science, recursive improvement, and experimental AI governance.
Robot Judgment OS Lab: Designing Responsibility-Bounded Physical-World AI with Multi-Universe Gates
An agentic R&D team architecture for robot governance research — two lab divisions, eleven specialized agents, and five research themes bridging MARIA OS Multi-Universe evaluation with physical-world robotic systems
Physical-world robots demand governance architectures that digital-only agent systems cannot provide: sub-millisecond fail-closed gates, real-time multi-universe conflict detection, embodied ethical learning under sensor noise, and quantitative human-robot responsibility allocation at every decision node. This paper presents the Robot Judgment OS Lab — an agentic R&D team design embedded within the MARIA OS coordinate system, organized into two divisions (Robot Gate Architecture Lab and Embodied Learning & Conflict Lab) with eleven specialized agents operating under fail-closed research gates. We formalize five research themes: Responsibility-Bounded Robot Decision, Physical-World Conflict Mapping, Embodied Ethical Learning, Human-Robot Responsibility Matrix, and ROS2 Multi-Universe Bridge. Mathematical contributions include a real-time ConflictScore function, constrained RL for embodied ethics calibration, a four-factor responsibility decomposition protocol, safety-bounded action spaces, and a layered architecture formalization from ROS2 base through Multi-Universe, Gate, and Conflict layers. The lab design demonstrates that structured R&D governance — where research teams are themselves governed by the infrastructure they study — produces faster, safer, and more auditable advances in robot judgment than traditional unstructured robotics research.
Responsible Robot Judgment OS: Multi-Universe Gate Control for Physical-World Autonomous Decision Systems
Extending fail-closed responsibility gates from digital agents to physical-world robotic systems
Physical-world robots operate under hard real-time constraints where fail-closed gates must halt actuators within milliseconds. This paper introduces a multi-universe evaluation architecture for robotic decision systems across Safety, Regulatory, Efficiency, Ethics, and Human Comfort universes. We analyze how responsibility-bounded judgment can be maintained under latency constraints, sensor noise, and embodied ethical drift, and describe components including a Robot Gate Engine, real-time conflict heatmap, ethics-calibration model, responsibility protocol, and a layered architecture bridging MARIA OS with ROS2.