Talk is Cheap, Communication is Hard: Dynamic Grounding Failures and Repair in Multi-Agent Negotiation

2026-05-03

AI Summary

This study addresses the challenge that multi-agent systems often fail to achieve Pareto optimality in dynamic negotiation due to an inability to establish mutual understanding. The authors design a multi-round resource allocation negotiation game and, for the first time, systematically identify and categorize four failure modes in dynamic grounding. They propose a quantifiable framework to decompose coordination gaps and investigate them through large language model–based multi-agent simulations, contextual ablation studies, and transparent intervention experiments. Results reveal that even with full information exchange, peer agent pairs frequently fail to converge to known optimal solutions, demonstrating that effective coordination depends not merely on the presence of communication but critically on aligned semantic foundations.

Abstract

Grounding is the collaborative process of establishing mutual belief sufficient for the current communicative purpose. While static grounding maps language to a shared, externally observable context, dynamic grounding is a joint activity where meaning is negotiated through interaction. Current multi-agent Large Language Model (LLM) benchmarks focus on static, one-shot tasks, overlooking the ability to repair grounding breakdowns across turns. We introduce an iterated, multi-turn negotiation game in which two agents allocate shared resources toward private projects with verifiable jointly optimal outcomes. While individual agents can identify Pareto-optimal allocations in isolation, agent dyads consistently fail to reach them across open- and closed-source models. Our investigation reveals four failure modes: (1) coordination degrades when shared interaction history is absent; (2) yet accumulated context can itself become a liability through stubborn anchoring, where initial proposals are treated as axiomatic rather than negotiable; (3) a reliance on perfunctory fairness (equal resource splits) over reward-maximizing coordination; and (4) failures in referential binding, where agents lose track of commitments across turns. These results highlight dynamic grounding as a critical and understudied axis of multi-agent coordination. Our framework decomposes the coordination gap into measurable components: the oracle baseline establishes that the gap is not attributable to individual reasoning limitations; the no-talk baseline establishes that communication is necessary; and a full-transparency intervention establishes that information exchange alone is insufficient: the bottleneck lies in the interactive processes of joint plan formation, commitment, and execution that constitute dynamic grounding.

Problem

• dynamic grounding
• multi-agent negotiation
• grounding failures
• communication repair
• coordination

Innovation

• dynamic grounding
• multi-agent negotiation
• grounding failures
• iterated interaction
• referential binding