发表机构
College of Computing, Georgia Institute of Technology（佐治亚理工学院计算学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究构建了名为WOPR的社会模拟环境，以兵棋推演为载体，采用Concordia为默认工具，实现了带有可验证规则引擎和四级沟通阶梯的模拟系统，将军事决策等战略选择转化为智能体的明确决策。
AI 中文摘要
WOPR是一个用于研究组织如何做出高风险决策的社会模拟环境，它基于确定性的、经重播验证的规则引擎构建，并以兵棋推演作为载体。我们首先将其实例化为已公开的卡牌游戏《核战争》（Nuclear War），并对照其已发布的规则进行验证。我们选择从军事决策入手，是因为其具有安全层面的意义且需要进一步研究，但该设计并非仅针对军事领域：将引擎暴露给智能体的决策点契约可在可验证规则系统中重复使用。现有社会模拟工作强调角色真实性和合成观点，但缺乏带有重播可验证机制及私人渠道协商的可验证规则引擎。WOPR提供了这一引擎，且其契约使每一个战略选择都成为明确的智能体决策。该方法与社会模拟框架无关；我们采用Concordia作为驱动游戏的默认工具。在同一引擎上，WOPR分层构建了一个四级沟通阶梯，从沉默到带有结构化承诺的私人单接收者渠道，并将每个派系实例化为集体指挥控制系统而非单一智能体。我们将所有代码、示例配置及重播数据公开提供于此https URL。
英文摘要
WOPR is a social-simulation environment for studying how organizations make high-stakes decisions, built on a deterministic, replay-validated rules engine and using wargames as the vehicle. We instantiate it first with the published card game Nuclear War, traced against its published rules. We start with military decision-making because of its safety implications and because it needs further study, but the design is not specific to it: the decision-point contract that exposes the engine to agents is reusable across verifiable rule systems. Existing social-simulation work emphasizes persona fidelity and synthetic opinion, but lacks a verifiable rules engine with replay-checkable mechanics and private-channel negotiation. WOPR supplies that engine, and its contract makes every strategic choice an explicit agent decision. The method is agnostic to social-simulation frameworks; we adopt Concordia as the default harness for driving the game. On the same engine, WOPR layers a four-rung press ladder from silence to private single-recipient channels with structured commitments, and instantiates each faction as a collective command-and-control system rather than a single agent. We make all code, example configurations, and replay data publicly available at https://github.com/eilab-gt/wopr.
Comments16 pages, 11 figures. Published at the Social Sim'26 Workshop at COLM 2026. Code and replay data: https://github.com/eilab-gt/wopr
