[2603.21696] MIND: Multi-agent inference for negotiation dialogue in travel planning

Computer Science > Artificial Intelligence arXiv:2603.21696 (cs) [Submitted on 23 Mar 2026] Title:MIND: Multi-agent inference for negotiation dialogue in travel planning Authors:Hunmin Do, Taejun Yoon, Kiyong Jung View a PDF of the paper titled MIND: Multi-agent inference for negotiation dialogue in travel planning, by Hunmin Do and 2 other authors View PDF HTML (experimental) Abstract:While Multi-Agent Debate (MAD) research has advanced, its efficacy in coordinating complex stakeholder interests such as travel planning remains largely unexplored. To bridge this gap, we propose MIND (Multi-agent Inference for Negotiation Dialogue), a framework designed to simulate realistic consensus-building among travelers with heterogeneous preferences. Grounded in the Theory of Mind (ToM), MIND introduces a Strategic Appraisal phase that infers opponent willingness (w) from linguistic nuances with 90.2% accuracy. Experimental results demonstrate that MIND outperforms traditional MAD frameworks, achieving a 20.5% improvement in High-w Hit and a 30.7% increase in Debate Hit-Rate, effectively prioritizing high-stakes constraints. Furthermore, qualitative evaluations via LLM-as-a-Judge confirm that MIND surpasses baselines in Rationality (68.8%) and Fluency (72.4%), securing an overall win rate of 68.3%. These findings validate that MIND effectively models human negotiation dynamics to derive persuasive consensus. Comments: Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2603.2169...