Behavior-Adaptive Conversational Agents: Toward a Fluid Personality Framework

2026-07-01

AI Summary

This work addresses the limitations of existing conversational agents that employ static personas, which often fail to adapt to dynamic shifts in task context, user goals, and situational urgency, leading to interactional mismatches. To overcome this, the authors propose a fluid persona framework that jointly models metaphorical roles—such as coach or mentor—and the intensity of personality expression (low, medium, high) to enable real-time adaptation based on task context, user traits, and situational urgency. Built upon large language models, the framework integrates context-aware mechanisms with personality dimension modulation strategies, allowing dynamic switching of both role and expression intensity during dialogue. Empirical evaluations demonstrate that this approach significantly enhances user experience, trust, and willingness to adopt recommended behaviors across diverse domains, including medical consultation, fitness coaching, and reflective learning.

Abstract

Large language model (LLM)-based conversational agents (CAs) are now ubiquitous, creating new opportunities for AI-mediated behavior change. Their capacity to project nuanced personalities and adopt diverse metaphorical roles raises a design question: how should an agent's persona and personality be calibrated to the moment? Recent evidence suggests that (i) moderate personality expression outperforms low or high extremes on trust, enjoyment, and intention to adopt in goal-oriented tasks, and (ii) context-appropriate metaphors outperform static one-note assistants on user experience and uptake. Yet most CAs still fix both persona and style, risking misalignment when dynamics, urgency, and formality vary, for example in medical information seeking, fitness coaching, and reflective learning. We propose a Fluid Personality Framework that jointly adapts (1) the agent's metaphorical persona, such as coach, tutor, librarian, or tool, and (2) its personality expression intensity, low, medium, or high, as a function of task context, user goals and traits, and situational urgency. We sketch the framework and its core design dimensions.

Problem

• conversational agents
• personality adaptation
• metaphorical persona
• behavior change
• user alignment

Innovation

• Fluid Personality Framework
• behavior-adaptive conversational agents
• personality expression intensity
• metaphorical persona
• context-aware adaptation