寻求共识的论证：在冲突个体间寻找可能的共识区
Argumentation for Common Ground: Finding Zones of Possible Agreement between Individuals in Conflict
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中文总结 AI 辅助
本文提出定量双极论证框架，通过合并冲突双方的推理框架识别可能的共识区（ZOPA），并以巴以冲突的调查数据验证其可行性，为冲突解决提供新方法。
中文摘要 AI 辅助
当公民对和平协议的接受度受争议性叙事影响时，如何识别冲突社会间的共识？这种接受度不仅取决于协议包含或排除的条款，更关键的是公民对协议条款的主观推理。本文利用计算论证，提出一种识别冲突个体间相互可接受协议的新方法，即可能的共识区（ZOPA）。首先，引入一种定量双极论证框架，用于呈现各方对和平协议的推理；接着，展示合并这些框架如何让谈判者识别出相互可接受的和平协议。为在现实相关条件下评估该方法，研究聚焦巴以冲突，长期的政策、从业者及公众需求凸显了对分析极化公共推理方法的要求。通过理论分析及使用既有研究的调查数据与大语言模型检索数据的初步实验，展示该框架如何识别ZOPA。结果表明，论证能助力谈判者与冲突解决团队绘制基于公民推理的可行ZOPA。
英文摘要
How can common ground between societies in conflict be identified when citizens' acceptability of peace agreements is shaped by contested narratives? Such acceptability is mediated not only by the clauses that agreements include or exclude, but crucially by citizens' subjective reasoning concerning agreements' clauses. In this paper, we leverage computational argumentation to introduce a novel approach to identifying mutually acceptable agreements among individuals in conflict, i.e. a Zone of Possible Agreement (ZOPA). First, we introduce a quantitative bipolar argumentation framework tailored to represent each side's reasoning about peace agreements. We then show how merging these frameworks can enable negotiators to identify peace agreements that are mutually acceptable. To evaluate our approach under conditions of real-world relevance, we focus on the Palestinian-Israeli conflict, where long-standing policy, practitioner and public interest underscores the demand for methods capable of analysing polarised public reasoning. We show how our framework identifies a ZOPA through theoretical analysis and preliminary experiments using survey data from both existing work and retrieved by a large language model. The results illustrate how argumentation can empower negotiators and conflict-resolution teams in mapping feasible ZOPAs grounded in citizens' reasoning.
