网络-物理-社会-思维空间中agi驱动的情感计算:框架、技术、应用和未来方向

IF 18.8 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Artificial Intelligence Review Pub Date : 2026-08-27 Epub Date: 2026-08-31 DOI:10.1007/s10462-026-11691-7
Feifei Shi, Jingyi Yang, Zita Lifelo, Jianguo Ding, Huansheng Ning
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引用次数: 0

摘要

通用人工智能(AGI)的出现有望彻底改变情感计算。然而,目前的研究缺乏一个系统的框架来解释人类情感固有的跨空间性质,即生理状态(物理空间)、文化规范(社会空间)、认知过程(思维空间)和数字数据(网络空间)不断地相互作用和塑造。为了解决这一差距,本文首先在网络-物理-社会-思维(CPST)空间理论中重新定位情感计算,将其概念化为跨空间转换的动态过程,而不是孤立的功能。AGI的感知、学习、推理、记忆、泛化和生成能力作为实现这些跨空间转换的计算引擎。然后,我们系统地将AGI技术(例如,因果建模、思维链、扩散模型)映射到特定的情感计算任务,并展示每种技术如何支持它们的实现。通过整合CPST作为理论支柱和AGI作为使能技术,本文为下一代情感计算提供了系统的路线图。讨论了潜在的应用和未来的方向,强调了这个框架如何将人类水平的情感智能推进到真正的同理心和情境意识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Agi-powered affective computing in cyber-physical-social-thinking space: framework, techniques, applications and future directions

The advent of Artificial General Intelligence (AGI) promises to revolutionize affective computing. However, current research lacks a systematic framework that accounts for the inherently cross-space nature of human emotion, where physiological states (physical space), cultural norms (social space), cognitive processes (thinking space), and digital data (cyberspace) continuously interact and shape each other. To address this gap, this paper starts by repositioning affective computing within the theory of Cyber-Physical-Social-Thinking (CPST) space, conceptualizing it as a dynamic process of cross-space transformation rather than an isolated function. AGI capabilities of perception, learning, reasoning, memory, generalization, and generation serve as the computational engines that enable these cross-space transformations. We then systematically map AGI techniques (e.g., causal modeling, chain-of-thought, diffusion models) to specific affective computing tasks, showing how each technique supports their realization. By integrating CPST as a theoretical backbone and AGI as an enabling technology, this paper provides a systematic roadmap for next-generation affective computing. Potential applications and future directions are also discussed, highlighting how this framework advances human-level affective intelligence toward genuine empathy and contextual awareness.

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来源期刊
Artificial Intelligence Review
Artificial Intelligence Review 工程技术-计算机:人工智能
CiteScore
22.00
自引率
3.30%
发文量
194
审稿时长
5.3 months
期刊介绍: Artificial Intelligence Review, a fully open access journal, publishes cutting-edge research in artificial intelligence and cognitive science. It features critical evaluations of applications, techniques, and algorithms, providing a platform for both researchers and application developers. The journal includes refereed survey and tutorial articles, along with reviews and commentary on significant developments in the field.
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