Cooperative AI: machines must learn to find common ground
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DOI: 10.1038/d41586-021-01170-0
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Cited by:
- Kinga Makovi & Anahit Sargsyan & Wendi Li & Jean-François Bonnefon & Talal Rahwan, 2023. "Trust within human-machine collectives depends on the perceived consensus about cooperative norms," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
- Luyao Zhang & Xinyu Tian, 2022. "On Blockchain We Cooperate: An Evolutionary Game Perspective," Papers 2212.05357, arXiv.org, revised Jan 2023.
- Cimpeanu, Theodor & Di Stefano, Alessandro & Perret, Cedric & Han, The Anh, 2023. "Social diversity reduces the complexity and cost of fostering fairness," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
- Wolfram Barfuss & Janusz Meylahn, 2022. "Intrinsic fluctuations of reinforcement learning promote cooperation," Papers 2209.01013, arXiv.org, revised Feb 2023.
- János Kramár & Tom Eccles & Ian Gemp & Andrea Tacchetti & Kevin R. McKee & Mateusz Malinowski & Thore Graepel & Yoram Bachrach, 2022. "Negotiation and honesty in artificial intelligence methods for the board game of Diplomacy," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
- Noblit, Graham Alexander & Hadfield, Gillian, 2023. "Normative Conflict and Normative Change," SocArXiv tvg7b, Center for Open Science.
- Daphne Cornelisse & Thomas Rood & Mateusz Malinowski & Yoram Bachrach & Tal Kachman, 2022. "Neural Payoff Machines: Predicting Fair and Stable Payoff Allocations Among Team Members," Papers 2208.08798, arXiv.org.
- Rebecca Sarku & Ulfia A. Clemen & Thomas Clemen, 2023. "The Application of Artificial Intelligence Models for Food Security: A Review," Agriculture, MDPI, vol. 13(10), pages 1-28, October.
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Keywords
Machine learning; Computer science; Society; Technology; Sociology; Human behaviour;All these keywords.
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