面向分布式控制与智能体交互的动作导向信息
Action-Directed Information for Distributed Control and Agentic Interaction
- University of California San Diego（加州大学圣地亚哥分校）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出一种在消息改变接收动作的界面处测量信息的方法，以研究分布式控制系统，并在DI-Walker中验证，发现同伴传感器在复合故障下具有优势，揭示了中间控制动作信息的隐藏效应。
AI中文摘要：
分布式智能涉及这样的系统：具有局部动力学和部分观测的半自主组件通过信息交换进行协调，以维持共享功能。本文提出了一种研究此类系统的操作性方法：在消息改变接收动作的界面处测量信息，然后通过干预和扰动评估将该测量与功能联系起来。我们在DI-Walker中实例化了这一提议，这是一个由冻结的交叉熵方法策略控制的二维四肢体具身植物。我们比较了使用每个肢体自身实现力传感器的控制器与使用同伴肢体实现力传感器的控制器。在肢体缺失、肢体滑动和弱中央控制丢失的情况下，Peer-Sensor在若干条件下具有较低的后期跟踪误差。一个修正的有限历史动作预测估计器在复合故障下显示出显著更大的同伴消息增益。一个未来的标量功能预测估计器没有显示出同样的稳定优势。我们将这种差异解释为一个方法论结果：对中间控制动作有用的信息可能被后来的植物动力学、冗余和上下文所隐藏。本文将这一结果与预测信息、转移熵、有向信息、信息到去/IT-PAC思想、赋权以及鲁棒控制数据率视角联系起来，同时明确区分了操作预测增益与精确有向信息、信道容量和正式数据率定理。
英文摘要：
Distributed intelligence concerns systems in which semi-autonomous components with local dynamics and partial observations coordinate through information exchange to maintain a shared function. This paper proposes an operational way to study such systems: measure information at the interface where a message changes a receiving action, then connect that measure to function by intervention and disturbance evaluation. We instantiate this proposal in DI-Walker, a two-dimensional four-limb embodied plant controlled by frozen Cross-Entropy-Method policies. We compare a controller using each limb's own realized-force sensor with one using the realized-force sensors of peer limbs. Under limb loss, limb slip, and weak central-control dropout, Peer-Sensor has lower late tracking error in several conditions. A corrected finite-history action-predictive estimator shows a substantially larger peer-message gain under compound failure. A future scalar functional-prediction estimator does not show the same stable advantage. We interpret this discrepancy as a methodological result: information useful for an intermediate control action can be hidden by later plant dynamics, redundancy, and context. The paper relates this result to Predictive Information, Transfer Entropy, Directed Information, information-to-go/IT-PAC ideas, empowerment, and the robust control data-rate perspective, while explicitly distinguishing operational predictive gains from exact Directed Information, channel capacity, and a formal data-rate theorem.
