目的论驱动的情感计算：以对齐福祉为目标的因果框架

his paper provides a systematic review and reflection on the major achievements and shortcomings of contemporary emotion theory and affective computing from a teleological perspective and proposes a novel framework of "teleology-driven affective computing". First, the paper re-examines mainstream theories such as basic emotions, appraisal theory, and constructivism from the evolutionary functional perspective, emphasizing that the core of affect is to help organisms adapt to their environment and achieve their goals. Although existing research on affective computing has made significant progress in areas like multimodal emotion recognition and emotion generation driven by appraisal theory, it primarily focuses on pattern recognition of external features and lacks a systematic response framework that addresses the emotional dynamics and multi-level needs at both individual and group levels. To address this, the paper advocates for aligning individual and group welfare as the central goal, and proposes two key steps at the algorithmic level to achieve this: First, causal modeling based on real affective event data from individuals to generate virtual environments that accurately simulate individual emotional and behavioral dynamics; second, utilizing meta-reinforcement learning to conduct continuous training in this environment, enabling affective agents to learn to balance short-term and long-term needs and quickly adapt to personalized concerns in different contexts. The specific approach includes constructing a large-scale "personal affective event dataverse" to support causal structure learning, and during the training phase, designing reasonable reward functions that internalize the goal of "helping users achieve sustained and broader positive experiences" as the primary objective of the agent, while balancing different emotional needs across spatial and temporal dimensions and group scales. The paper also highlights that achieving coordination between diverse needs and social equity remains a critical challenge that requires further integration of psychology and sociology theories. Overall, the teleology-driven affective computing framework lays the foundation for intelligent agents emotional cognition and deep empathy based on individual and group needs, demonstrating the potential value in advancing the integration of human-computer interaction and societal well-being.