Hughes, Edward

Multi-Agent Risks from Advanced AI

Hammond, L., Chan, A., Clifton, J., Hoelscher-Obermaier, J., Khan, A., McLean, E., Smith, C., Barfuss, W., Foerster, J., Gavenčiak, T., et al. (2025) · arXiv

Ethics and Social Impacts of AIMulti-Agent Systems and Negotiation

Cited by 305

Inequity aversion improves cooperation in intertemporal social dilemmas

Hughes, E., Leibo, J. Z., Phillips, M. G., Tuyls, K., Duéñez-Guzmán, E. A., Castañeda, A. G., Dunning, I., Zhu, T., McKee, K. R., Koster, R., et al. (2018) · arXiv

Evolutionary Game Theory and CooperationExperimental Behavioral Economics Studies

Cited by 134

Open Problems in Cooperative AI

Dafoe, A., Hughes, E., Bachrach, Y., Collins, T., McKee, K. R., Leibo, J. Z., Larson, K., & Graepel, T. (2020) · arXiv

Multi-Agent Systems and NegotiationGame Theory and Voting Systems

Cited by 93

Causal Reasoning from Meta-reinforcement Learning

Dasgupta, I., Wang, J., Chiappa, S., Mitrovic, J., Ortega, P., Raposo, D., Hughes, E., Battaglia, P., Botvinick, M., & Kurth-Nelson, Z. (2019) · arXiv

Reinforcement Learning in RoboticsBayesian Modeling and Causal Inference

Cited by 71

Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research

Leibo, J. Z., Hughes, E., Lanctot, M., & Graepel, T. (2019) · arXiv

Complex Systems and DynamicsMulti-Agent Systems and Negotiation

Cited by 60

The Ethics of Advanced AI Assistants

Gabriel, I., Manzini, A., Keeling, G., Hendricks, L. A., Rieser, V., Iqbal, H., Tomašev, N., Ktena, I., Kenton, Z., Rodriguez, M., et al. (2024) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 57

Social Diversity and Social Preferences in Mixed-Motive Reinforcement Learning

McKee, K. R., Gemp, I., McWilliams, B., Duèñez-Guzmán, E. A., Hughes, E., & Leibo, J. Z. (2020) · International Joint Conference on Autonomous Agents and Multiagent Systems

Reinforcement Learning in RoboticsExperimental Behavioral Economics Studies

Cited by 33

Genie: Generative Interactive Environments

Bruce, J., Dennis, M., Edwards, A., Parker-Holder, J., Shi, Y., Hughes, E., Lai, M., Mavalankar, A., Steigerwald, R., Apps, C., et al. (2024) · arXiv

Reinforcement Learning in RoboticsGenerative Adversarial Networks and Image Synthesis

Cited by 23

Olympiad-level formal mathematical reasoning with reinforcement learning

Hubert, T., Mehta, R., Sartran, L., Horváth, M. Z., Žužić, G., Wieser, E., Huang, A., Schrittwieser, J., Schroecker, Y., Masoom, H., et al. (2026) · Nature

Artificial Intelligence ApplicationsMathematics, Computing, and Information Processing

Cited by 19

Learning Reciprocity in Complex Sequential Social Dilemmas

Eccles, T., Hughes, E., Kramár, J., Wheelwright, S., & Leibo, J. Z. (2019) · arXiv

Evolutionary Game Theory and CooperationExperimental Behavioral Economics Studies

Cited by 19

Human-Timescale Adaptation in an Open-Ended Task Space

Adaptive Agent Team, Bauer, J., Baumli, K., Baveja, S., Behbahani, F., Bhoopchand, A., Bradley-Schmieg, N., Chang, M., Clay, N., Collister, A., et al. (2023) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 19

Learning few-shot imitation as cultural transmission

Bhoopchand, A., Brownfield, B., Collister, A., Dal Lago, A., Edwards, A., Everett, R., Fréchette, A., Oliveira, Y. G., Hughes, E., Mathewson, K. W., et al. (2023) · Nature Communications

Language and cultural evolutionReinforcement Learning in Robotics

Cited by 14

Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning

Cook, J., Lu, C., Hughes, E., Leibo, J. Z., & Foerster, J. (2024) · arXiv

Reinforcement Learning in RoboticsEvolutionary Algorithms and Applications

Cited by 6

A multi-agent reinforcement learning model of reputation and cooperation in human groups

McKee, K. R., Hughes, E., Zhu, T. O., Chadwick, M. J., Koster, R., Castaneda, A. G., Beattie, C., Graepel, T., Botvinick, M., & Leibo, J. Z. (2021) · arXiv

Evolutionary Game Theory and CooperationExperimental Behavioral Economics Studies

Cited by 5

Open-Endedness is Essential for Artificial Superhuman Intelligence

Hughes, E., Dennis, M., Parker-Holder, J., Behbahani, F., Mavalankar, A., Shi, Y., Schaul, T., & Rocktaschel, T. (2024) · arXiv

Psychiatry, Mental Health, NeuroscienceArtificial Intelligence Applications

Cited by 4