Multi-agent, human–agent and beyond: A survey on cooperation in social dilemmas

IF 5.5 2区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Neurocomputing Pub Date : 2024-09-06 DOI:10.1016/j.neucom.2024.128514

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引用次数: 0

Abstract

The study of cooperation within social dilemmas has long been a fundamental topic across various disciplines, including computer science and social science. Recent advancements in Artificial Intelligence (AI) have significantly reshaped this field, offering fresh insights into understanding and enhancing cooperation. This survey examines three key areas at the intersection of AI and cooperation in social dilemmas. First, focusing on multi-agent cooperation, we review the intrinsic and external motivations that support cooperation among rational agents, and the methods employed to develop effective strategies against diverse opponents. Second, looking into human–agent cooperation, we discuss the current AI algorithms for cooperating with humans and the human biases towards AI agents. Third, we review the emergent field of leveraging AI agents to enhance cooperation among humans. We conclude by discussing future research avenues, such as using large language models, establishing unified theoretical frameworks, revisiting existing theories of human cooperation, and exploring multiple real-world applications.

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多代理、人类代理及其他：社会困境中的合作调查

长期以来，研究社会困境中的合作一直是包括计算机科学和社会科学在内的各个学科的基本课题。人工智能（AI）的最新进展极大地重塑了这一领域，为理解和加强合作提供了新的视角。本研究探讨了人工智能与社会困境中的合作之间的三个关键领域。首先，我们以多代理合作为重点，回顾了支持理性代理之间合作的内在和外在动机，以及针对不同对手制定有效策略的方法。其次，在人类-代理合作方面，我们讨论了当前与人类合作的人工智能算法，以及人类对人工智能代理的偏见。第三，我们回顾了利用人工智能代理加强人类合作这一新兴领域。最后，我们讨论了未来的研究方向，如使用大型语言模型、建立统一的理论框架、重新审视现有的人类合作理论以及探索多种现实世界应用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Neurocomputing 工程技术-计算机：人工智能

CiteScore

13.10

自引率

10.00%

发文量

1382

审稿时长

70 days

期刊介绍： Neurocomputing publishes articles describing recent fundamental contributions in the field of neurocomputing. Neurocomputing theory, practice and applications are the essential topics being covered.