Preference Change

Preference change research investigates how and why individual preferences shift over time, focusing on modeling these dynamics to improve decision-making in various applications. Current research emphasizes developing robust algorithms and models, such as those incorporating contextual information, session-based learning, and meta-optimization techniques, to capture nuanced preference shifts and mitigate the impact of noisy data. This field is crucial for enhancing personalized recommendations, optimizing human-robot interaction, and building more effective and ethical AI systems that adapt to evolving user needs and avoid manipulative influences.