TRW: TRACE-RealWorld——作为物化视图的世界模型的可审计一致性契约
TRW: TRACE-RealWorld---An Auditable Consistency Contract for World Models as Materialized Views
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中文总结 AI 辅助
TRACE-RealWorld解决在变化物理世界中维护物化视图的问题，提出承诺级有效性抽象等数据管理方法，通过端到端评估测量多方面指标，贡献是为部署世界表示提供一致性、恢复和问责契约。
中文摘要 AI 辅助
TRACE-RealWorld解决了一个核心数据管理问题：当基础状态的读取存在定价、延迟、异构且不可靠时，在持续变化的物理世界上维护可操作的物化视图。其数据管理贡献包括物化预测的承诺级有效性抽象；后果条件自适应视图维护；授权后无效承诺的事务式、依赖范围补偿；以及支持精确重放的仅追加溯源。该工作直接基于物化视图维护、自适应流同步、事务恢复、saga、数据新鲜度和溯源。通过六个预注册问题和留出的种子进行的端到端Flood-SAR评估将传感视为物理数据采集，并测量新鲜度、验证成本、过时读取、恢复范围、恢复失败和可重放性。因此，其贡献不是一个新的预测模型，而是将学习到的世界表示部署为运营数据系统的一致性、恢复和问责契约。
英文摘要
World models let agents plan against predicted physical state, but that state drifts; re-observation is costly and delayed, and repair can fail. We present TRACE-RealWorld (TRW), to our knowledge the first commitment-level consistency contract for world models. TRW treats predicted state as a materialized view and a physical commitment as a read whose authorization can expire. Typed, calibrated claims specify consequence-conditioned freshness and priced verification. Adaptive refresh generalizes dual-Kalman synchronization to consult the world when evidence could change a decision; dependency-scoped SagaLLM compensation repairs reversible commitments invalidated after authorization. Under an event-aligned risk oracle and recovery-liveness assumptions, we prove that synchronization and compensation are insufficient alone, whereas their composition gives a conditional consistency guarantee. Otherwise, the argument yields an auditable decomposition of violations into named debts. We implement TRW in Flood-SAR, a search-and-rescue simulator over real geography, and test six preregistered questions at frozen operating points on held-out seeds. Adaptive refresh reduces stale execution but does not dominate fixed refresh on cost, coverage, or rescue outcomes. Localized repair reduces repair work by 9.56 units per mission and restoration latency by 80.7 seconds relative to global recovery; the observed residual-violation difference is zero without establishing equivalence. Detection coverage is 0.83-0.89, and 10 of 97 invoked restorations are incomplete by mission end. The campaign treats empirical slack as sensitivity inputs rather than discharging the theorem's assumptions or providing a simultaneous population certificate. Exact replay reconstructs a disputed dispatch. TRW thus makes a world model an auditable predictive interface rather than a self-validating source of truth.
发表机构
- Stanford University（斯坦福大学）
机构由 AI 辅助整理，请以论文原文为准。
