  Previous research on persona-based dialogue agents typically preset the
agent's persona before deployment, which remains static thereafter. In this
paper, we take a step further and explore a new paradigm called Self-evolving
Personalized Dialogue Agents (SPDA), where the agent continuously evolves
during the conversation to better align with the user's anticipation by
dynamically adapting its persona. This paradigm could enable better
personalization for each user, but also introduce unique challenges, which
mainly lie in the process of persona adaptation. Two key issues include how to
achieve persona alignment with the user and how to ensure smooth transition in
the adaptation process. To address them, we propose a novel framework that
refines the persona at hierarchical levels to progressively align better with
the user in a controllable way. Experiments show that integrating the personas
adapted by our framework consistently enhances personalization and overall
dialogue performance across various base systems.
