The Convention Gap: Beyond Literal Content in Human-AI Cooperation
Cooperative AI agents are often evaluated against other AIs, yet human cooperation is thought to rely on implicit conventions: shared rules for reading meaning beyond the literal message. We propose the convention gap as a diagnostic of such implicit communication. In the card game Hanabi, where hints are the only messages about one's own hand, the convention gap is the failure probability predicted exactly from the literal content of the hints and the visible cards, minus the observed failure rate of the cards played. We prove that the population gap (the value the gap approaches over many games) is zero when the partner's choices convey nothing beyond their literal content, given a fair...
| Authors | Makoto Fukushima, Hua-Dong Xiong, Ehsan Moradi Pari |
|---|---|
| Primary category | cs.AI |
| Published | 10 September 2026 |
| Last updated at source | 9 October 2026 |
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