[2604.07028] Strategic Persuasion with Trait-Conditioned Multi-Agent Systems for Iterative Legal Argumentation

Computer Science > Multiagent Systems arXiv:2604.07028 (cs) [Submitted on 8 Apr 2026] Title:Strategic Persuasion with Trait-Conditioned Multi-Agent Systems for Iterative Legal Argumentation Authors:Philipp D. Siedler View a PDF of the paper titled Strategic Persuasion with Trait-Conditioned Multi-Agent Systems for Iterative Legal Argumentation, by Philipp D. Siedler View PDF HTML (experimental) Abstract:Strategic interaction in adversarial domains such as law, diplomacy, and negotiation is mediated by language, yet most game-theoretic models abstract away the mechanisms of persuasion that operate through discourse. We present the Strategic Courtroom Framework, a multi-agent simulation environment in which prosecution and defense teams composed of trait-conditioned Large Language Model (LLM) agents engage in iterative, round-based legal argumentation. Agents are instantiated using nine interpretable traits organized into four archetypes, enabling systematic control over rhetorical style and strategic orientation. We evaluate the framework across 10 synthetic legal cases and 84 three-trait team configurations, totaling over 7{,}000 simulated trials using DeepSeek-R1 and Gemini~2.5~Pro. Our results show that heterogeneous teams with complementary traits consistently outperform homogeneous configurations, that moderate interaction depth yields more stable verdicts, and that certain traits (notably quantitative and charismatic) contribute disproportionately to persuasive succes...