mlsanityData to 14 Oct 2026

No One Wins in Nuclear War: A Social Simulation of Military Decision-making

arXiv 2608.01868 ↗First posted 3 Aug 2026cs.CY cs.AI cs.CLcited by 0

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 8 of its 22 references that are in the map. First posted on arXiv 3 Aug 2026.

Builds on

8 of 22 references.

References · 8

  1. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,568
  2. 2023Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordiacited by 126
  3. 2024Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agentscited by 125
  4. 2024Escalation Risks from Language Models in Military and Diplomatic Decision-Makingcited by 63
  5. 2025SimBench: Benchmarking the Ability of Large Language Models to Simulate Human Behaviorscited by 52
  6. 2024Human vs. Machine: Behavioral Differences Between Expert Humans and Language Models in Wargame Simulationscited by 21
  7. 2024Open-Ended Wargames with Large Language Modelscited by 8
  8. 2025NegotiationGym: Self-Optimizing Agents in a Multi-Agent Social Simulation Environmentcited by 3

Built on by

Not cited yet.