标题： 仿生强化学习中的功能情绪建模 显示英文标题

标题： Functional Emotion Modeling in Biomimetic Reinforcement Learning

摘要： 我们通过采用一个假设——初始的一组假设——来探索情绪的功能主义方法，即假设概念生成模型包含未经证实但具有生物学合理性的特征。 从这些特征出发，我们数学上构建了一个基于功能主义原则的理论强化学习框架，并研究由此产生的效用函数如何与生物系统中的情感极性相一致。 我们的重点是通过概念网络来构建功能主义视角，特别强调效用函数的构建，而不是对情绪提供详尽的解释。 主要重点不是规划或行动执行，但当相关时会涉及这些因素。 最后，我们将该框架应用于幽默、反社会人格和广告等心理现象，展示了其解释能力的广度。 显示英文摘要

摘要： We explore a functionalist approach to emotion by employing an ansatz -- an initial set of assumptions -- that a hypothetical concept generation model incorporates unproven but biologically plausible traits. From these traits, we mathematically construct a theoretical reinforcement learning framework grounded in functionalist principles and examine how the resulting utility function aligns with emotional valence in biological systems. Our focus is on structuring the functionalist perspective through a conceptual network, particularly emphasizing the construction of the utility function, not to provide an exhaustive explanation of emotions. The primary emphasis is not of planning or action execution, but such factors are addressed when pertinent. Finally, we apply the framework to psychological phenomena such as humor, psychopathy, and advertising, demonstrating its breadth of explanatory power.