TAG ARCHIVE
conflict-mapping
MARIA OSブログのconflict-mappingタグに関連する2件の記事。ボンギンカンの判断OS、AIガバナンス、Agentic Company研究をテーマ別に参照しやすい技術記事アーカイブです。
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.
実行可能アーキテクチャとしての倫理: 多主体AI統治の計算可能制約化
宣言的倫理を、制約エンジン・ドリフト監視・検証サンドボックスへ落とし込む
倫理原則を運用可能にするため、数式制約化・時系列ドリフト検知・価値衝突可視化・監督整合評価を統合する。導入前シミュレーションで倫理影響を検証する実装フレームを示す。