用可组合的流水线验证多智能体系统的行为变化，提升推理透明度与可复用性。
Composable Verification Pipelines for Multi-Agent Systems
- 将动作语言语义转化为可执行的函数式流水线，分步处理状态与动作
- 支持模块化规格定义，确保验证流程终止且结果可追踪
- 适用于虚假信息传播、情绪推理等复杂场景，适合研究多智能体系统
现有针对行动与变化的推理方法通常基于逻辑编程系统，具备丰富的语义表达能力。本文提出一个基于Tiles的模块化框架，实现在Soda（一种高效函数式编程语言）中的转换与轨迹验证。该框架通过可组合的函数式组件，将状态、动作、转换和规则作为可执行的验证流水线处理，以类型化函数管道形式表示验证过程，实现模块化规格、可复用推理组件及透明执行流程，并保证流水线终止。框架包含可执行的规格层，用户可用YAML定义领域描述，自动转化为底层验证模型与可执行流水线结构。我们提供开源实现，并通过虚假信息传播与情感推理等案例展示其应用。
原文摘要 · Abstract (English)
Existing approaches for reasoning about action and change provide expressive semantics for modeling dynamic systems, in most cases built on top of logic programming systems. We introduce a modular framework for transition and trajectory verification based on Tiles and implemented in Soda, which is an efficient functional programming language. The framework operationalizes action language semantics through executable verification pipelines that process states, actions, transitions, and rules as compositional functional components. Verification procedures are represented as typed functional pipelines, enabling modular specifications, reusable reasoning components, and transparent execution workflows with guaranteed pipeline termination. The framework includes an executable specification layer that allows users to define domain descriptions in YAML, which are operationalized into the underlying verification model and executable pipeline structure. We provide an open-source implementation and illustrate the framework through examples that involve misinformation and emotional reasoning.
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