no code implementations • 26 Dec 2024 • Joel Z. Leibo, Alexander Sasha Vezhnevets, Manfred Diaz, John P. Agapiou, William A. Cunningham, Peter Sunehag, Julia Haas, Raphael Koster, Edgar A. Duéñez-Guzmán, William S. Isaac, Georgios Piliouras, Stanley M. Bileschi, Iyad Rahwan, Simon Osindero
Humans navigate a multi-scale mosaic of interlocking notions of what is appropriate for different situations.
1 code implementation • 6 Dec 2023 • Alexander Sasha Vezhnevets, John P. Agapiou, Avia Aharon, Ron Ziv, Jayd Matyas, Edgar A. Duéñez-Guzmán, William A. Cunningham, Simon Osindero, Danny Karmon, Joel Z. Leibo
Agent-based modeling has been around for decades, and applied widely across the social and natural sciences.
no code implementations • 29 May 2023 • Yiran Mao, Madeline G. Reinecke, Markus Kunesch, Edgar A. Duéñez-Guzmán, Ramona Comanescu, Julia Haas, Joel Z. Leibo
Is it possible to evaluate the moral cognition of complex artificial agents?
no code implementations • 1 May 2023 • Udari Madhushani, Kevin R. McKee, John P. Agapiou, Joel Z. Leibo, Richard Everett, Thomas Anthony, Edward Hughes, Karl Tuyls, Edgar A. Duéñez-Guzmán
In social psychology, Social Value Orientation (SVO) describes an individual's propensity to allocate resources between themself and others.
4 code implementations • 24 Nov 2022 • John P. Agapiou, Alexander Sasha Vezhnevets, Edgar A. Duéñez-Guzmán, Jayd Matyas, Yiran Mao, Peter Sunehag, Raphael Köster, Udari Madhushani, Kavya Kopparapu, Ramona Comanescu, DJ Strouse, Michael B. Johanson, Sukhdeep Singh, Julia Haas, Igor Mordatch, Dean Mobbs, Joel Z. Leibo
Melting Pot is a research tool developed to facilitate work on multi-agent artificial intelligence, and provides an evaluation protocol that measures generalization to novel social partners in a set of canonical test scenarios.
no code implementations • 5 Jan 2022 • Kavya Kopparapu, Edgar A. Duéñez-Guzmán, Jayd Matyas, Alexander Sasha Vezhnevets, John P. Agapiou, Kevin R. McKee, Richard Everett, Janusz Marecki, Joel Z. Leibo, Thore Graepel
A key challenge in the study of multiagent cooperation is the need for individual agents not only to cooperate effectively, but to decide with whom to cooperate.
no code implementations • 21 Oct 2021 • Edgar A. Duéñez-Guzmán, Kevin R. McKee, Yiran Mao, Ben Coppin, Silvia Chiappa, Alexander Sasha Vezhnevets, Michiel A. Bakker, Yoram Bachrach, Suzanne Sadedin, William Isaac, Karl Tuyls, Joel Z. Leibo
Undesired bias afflicts both human and algorithmic decision making, and may be especially prevalent when information processing trade-offs incentivize the use of heuristics.
1 code implementation • 13 Nov 2020 • Charles Beattie, Thomas Köppe, Edgar A. Duéñez-Guzmán, Joel Z. Leibo
We present DeepMind Lab2D, a scalable environment simulator for artificial intelligence research that facilitates researcher-led experimentation with environment design.
no code implementations • 6 Feb 2020 • Kevin R. McKee, Ian Gemp, Brian McWilliams, Edgar A. Duéñez-Guzmán, Edward Hughes, Joel Z. Leibo
Recent research on reinforcement learning in pure-conflict and pure-common interest games has emphasized the importance of population heterogeneity.
3 code implementations • NeurIPS 2018 • Edward Hughes, Joel Z. Leibo, Matthew G. Phillips, Karl Tuyls, Edgar A. Duéñez-Guzmán, Antonio García Castañeda, Iain Dunning, Tina Zhu, Kevin R. McKee, Raphael Koster, Heather Roff, Thore Graepel
Groups of humans are often able to find ways to cooperate with one another in complex, temporally extended social dilemmas.