Motivationally Grounded Role-Playing Agents: Stress-Driven Psychodynamic Modeling

Role-playing agents (RPAs) powered by large language models have become central to interactive character simulation, yet existing approaches often rely on surface-level persona descriptions and stylistic imitation, lacking a principled account of the internal psychological dynamics that drive role-consistent behavior. This limitation leads to shallow personality modeling and character drift in extended interactions. We propose a motivationally grounded framework that explicitly models a character's internal motivational structure. Grounded in psychodynamic, attachment, moral, existential, and interpersonal theories, we construct a structured character psychology that includes a taxonomy of core anxieties, a corresponding set of compensatory desires, three personality organization types, and a mapping from each personality organization and stress level to the character's available defense mechanisms. These structures are embedded in a dual-process generation architecture. On SocialBench, our method outperforms models of comparable scale. A controlled probe study on a purpose-built stress dataset further confirms that the framework's internal mechanisms operate as intended, with defense tier governing modulation intensity and defense selection producing distinct surface forms from the same impulse. These results suggest that explicitly modeling character psychology offers a scalable and effective pathway toward deeper role-playing fidelity.