Modeling Conflict De-Escalation in Shakespeare Through Hybrid NLP & Symbolic Approaches

Nicholas Sloss Treynor, Kyle Mitchell, Nick Toothman, Gina Bloom, Colin Milburn, Michael Neff, Joshua McCoy

Abstract: This demo paper presents an interactive narrative game where players intervene in Shakespearean scenes to deescalate imminent violence using natural speech. The system employs a hybrid architecture: modern natural language processing (NLP) tools (speech-to-text, large language models, sentence transformers) interpret user utterances for known de-escalation strategies (e.g., active listening, redirection) and gauge their effectiveness, while symbolic systems model character emotional stances, beliefs, and personality traits that affect input interpretation, in order to select fitting responses. The project contributes an investigation of current NLP capabilities for interactive character-driven games and serves a pedagogical purpose, teaching conflict resolution and violence prevention within a broader educational framework.

External IDs:dblp:conf/cig/TreynorMTBMNM25