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More Victories, Less Cooperation: Assessing Cicero's Diplomacy Play

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arxiv 2406.04643 v1 pith:HSNML3T2 submitted 2024-06-07 cs.CL

classification cs.CL
keywords cicerocommunicationdiplomacycommunicativeplayerscooperativehumanin-game
verification ladder T0 review T1 audit T2 compute T3 formal
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The boardgame Diplomacy is a challenging setting for communicative and cooperative artificial intelligence. The most prominent communicative Diplomacy AI, Cicero, has excellent strategic abilities, exceeding human players. However, the best Diplomacy players master communication, not just tactics, which is why the game has received attention as an AI challenge. This work seeks to understand the degree to which Cicero succeeds at communication. First, we annotate in-game communication with abstract meaning representation to separate in-game tactics from general language. Second, we run two dozen games with humans and Cicero, totaling over 200 human-player hours of competition. While AI can consistently outplay human players, AI-Human communication is still limited because of AI's difficulty with deception and persuasion. This shows that Cicero relies on strategy and has not yet reached the full promise of communicative and cooperative AI.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Democratizing Diplomacy: A Harness for Evaluating Any Large Language Model on Full-Press Diplomacy

    cs.AI 2025-08 conditional novelty 6.0 of 10

    An evaluation harness lets off-the-shelf local LLMs, including a 24B model, play full-press Diplomacy without fine-tuning.

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