D3C: Reducing the Price of Anarchy in Multi-Agent Learning

1 October 2020

Papers citing "D3C: Reducing the Price of Anarchy in Multi-Agent Learning"

10 / 10 papers shown

Title
Quantifying the Self-Interest Level of Markov Social Dilemmas Richard Willis Yali Du Joel Z Leibo Michael Luck 59 0 0 27 Jan 2025
Learning to Balance Altruism and Self-interest Based on Empathy in Mixed-Motive Games Fanqi Kong Yizhe Huang Song-Chun Zhu Siyuan Qi Xue Feng 31 2 0 10 Oct 2024
A social path to human-like artificial intelligence Edgar A. Duénez-Guzmán Suzanne Sadedin Jane X. Wang Kevin R. McKee Joel Z Leibo GNN 31 28 0 22 May 2024
Aligning Individual and Collective Objectives in Multi-Agent Cooperation Yang Li Wenhao Zhang Jianhong Wang Shao Zhang Yali Du Ying Wen Wei Pan 26 1 0 19 Feb 2024
Learning to Learn Group Alignment: A Self-Tuning Credo Framework with Multiagent Teams David Radke Kyle Tilbury 24 1 0 14 Apr 2023
Learning Roles with Emergent Social Value Orientations Wenhao Li Xiangfeng Wang Bo Jin J. Lu H. Zha 18 3 0 31 Jan 2023
The Importance of Credo in Multiagent Learning David Radke Kate Larson Timothy B. Brecht 32 11 0 15 Apr 2022
Warmth and competence in human-agent cooperation Kevin R. McKee Xuechunzi Bai S. Fiske 35 26 0 31 Jan 2022
Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment Michael Chang Sid Kaushik Sergey Levine Thomas L. Griffiths 31 8 0 28 Jun 2021
A learning agent that acquires social norms from public sanctions in decentralized multi-agent settings Eugene Vinitsky Raphael Köster J. Agapiou Edgar A. Duénez-Guzmán A. Vezhnevets Joel Z Leibo 27 37 0 16 Jun 2021