PsyBer-Agent: A Psychology-Driven User Agent for Recommender Systems
PsyBer-Agent introduces a psychology-inspired engine to simulate long-term user dynamics like fatigue and shifting preferences in recommender systems.
Current LLM-based simulators often fail to capture realistic user behavior over extended interaction cycles. PsyBer-Agent addresses this by modeling latent states—such as affect and fatigue—to better align simulated trajectories with real-world interaction logs.