发表机构
The University of Osaka（大阪大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对网络化物理人工智能中提案与物理行动间的验证间隙，提出后语义通信框架，通过区分证据传输与协调等机制，经实验揭示反馈的最终确定者依赖不对称性，并定义情节级报告模式以规范相关研究。
AI 中文摘要
一项任务有效的提案尚未成为合理的物理行动。在网络化物理人工智能中，提案可能被理解，但用于完成行动所需的有效、及时、与提案绑定的证据或权威仍然不可用，我们将这种不匹配称为验证间隙，并提出一种后语义通信框架，用于连接提案形成与物理执行的系统接口。该框架从应用声明的证据需求开始，将合格观测表示为证据记录，通过一条路径验证支持性和冲突性记录，并将证据充分性与授权最终确定及下游运行时门分离。它进一步区分证据传输（可扩大最终确定者可访问的记录集）与证据协调（可抑制最终确定端点已持有的记录周围的传输）。有限状态框架检查验证评估器是否一致实现了声明的区分。在声明的模型下，受控通信研究揭示了依赖最终确定者的不对称性：发送方最终确定的反馈使用证据传输在整个可行绘图区域内扩大证据可达性，而接收方最终确定的反馈使用协调抑制冗余有效载荷，直到丢失、延迟、新鲜度和截止日期成本将选择转向单向。最后，一个情节级报告模式为未来测量物理人工智能研究定义了共同基准。
英文摘要
A task-effective proposal is not yet a justified physical action. In networked Physical AI, a proposal may be understood while valid, timely, proposal-bound evidence or the authority required to finalize an action remains unavailable. We call this mismatch the verification gap and introduce a Post-Semantic Communication Framework for the systems interface between proposal formation and physical execution. The framework begins with application-declared evidence requirements, represents qualifying observations as evidence records, validates supporting and conflicting records through one path, and separates evidence sufficiency from authorized finalization and a downstream runtime gate. It further distinguishes evidence transfer, which can enlarge the record set reachable by a finalizer, from evidence coordination, which can suppress transmission around records already held at the finalization endpoint. Finite-state framework checks verify that the evaluator implements the declared distinctions consistently. Under the declared model, the controlled communication study exposes a finalizer-dependent asymmetry: sender-finalized Feedback uses evidence transfer to expand evidence reachability throughout the feasible plotted region, whereas receiver-finalized Feedback uses coordination to suppress redundant payload until loss, latency, freshness, and deadline costs shift selection to One-way. Finally, an episode-level reporting schema defines common denominators for future measured Physical-AI studies.
Comments9 pages, 3 figures, 3 tables
