Unsupervised measures for parameter selection of binarization algorithms. - Marte A. Ramírez-Ortegón; Edgar A. Duéñez-Guzmán; Raúl Rojas 001; Erik Cuevas (Pattern Recognit., 2011)

GESwarm: grammatical evolution for the automatic synthesis of collective behaviors in swarm robotics. - Eliseo Ferrante; Edgar A. Duéñez-Guzmán; Ali Emre Turgut; Tom Wenseleers (GECCO, 2013)

No Free Lunch and Benchmarks. - Edgar A. Duéñez-Guzmán; Michael D. Vose (Evol. Comput., 2013)

Evolution of Self-Organized Task Specialization in Robot Swarms. - Eliseo Ferrante; Ali Emre Turgut; Edgar A. Duéñez-Guzmán; Marco Dorigo; Tom Wenseleers (PLoS Comput. Biol., 2015)

A Lyapunov-based Approach to Safe Reinforcement Learning. - Yinlam Chow; Ofir Nachum; Edgar A. Duéñez-Guzmán; Mohammad Ghavamzadeh (NeurIPS, 2018)

Inequity aversion improves cooperation in intertemporal social dilemmas. - Edward Hughes 001; Joel Z. Leibo; Matthew Phillips; Karl Tuyls; Edgar A. Duéñez-Guzmán; Antonio García Castañeda; Iain Dunning; Tina Zhu; Kevin R. McKee; Raphael Koster; Heather Roff; Thore Graepel (NeurIPS, 2018)

Inequity aversion resolves intertemporal social dilemmas. - Edward Hughes 001; Joel Z. Leibo; Matthew G. Philips; Karl Tuyls; Edgar A. Duéñez-Guzmán; Antonio García Castañeda; Iain Dunning; Tina Zhu; Kevin R. McKee; Raphael Koster; Heather Roff; Thore Graepel (CoRR, 2018)

Malthusian Reinforcement Learning. - Joel Z. Leibo; Julien Pérolat; Edward Hughes 001; Steven Wheelwright; Adam H. Marblestone; Edgar A. Duéñez-Guzmán; Peter Sunehag; Iain Dunning; Thore Graepel (AAMAS, 2019)

Evolving Intrinsic Motivations for Altruistic Behavior. - Jane X. Wang; Edward Hughes 001; Chrisantha Fernando; Wojciech M. Czarnecki; Edgar A. Duéñez-Guzmán; Joel Z. Leibo (AAMAS, 2019)

Lyapunov-based Safe Policy Optimization for Continuous Control. - Yinlam Chow; Ofir Nachum; Aleksandra Faust; Mohammad Ghavamzadeh; Edgar A. Duéñez-Guzmán (CoRR, 2019)

Neural Replicator Dynamics: Multiagent Learning via Hedging Policy Gradients. - Daniel Hennes; Dustin Morrill; Shayegan Omidshafiei; Rémi Munos; Julien Pérolat; Marc Lanctot; Audrunas Gruslys; Jean-Baptiste Lespiau; Paavo Parmas; Edgar A. Duéñez-Guzmán; Karl Tuyls (AAMAS, 2020)

Social Diversity and Social Preferences in Mixed-Motive Reinforcement Learning. - Kevin R. McKee; Ian Gemp; Brian McWilliams; Edgar A. Duéñez-Guzmán; Edward Hughes 001; Joel Z. Leibo (AAMAS, 2020)

Safe Policy Learning for Continuous Control. - Yinlam Chow; Ofir Nachum; Aleksandra Faust; Edgar A. Duéñez-Guzmán; Mohammad Ghavamzadeh (CoRL, 2020)

Model-free conventions in multi-agent reinforcement learning with heterogeneous preferences. - Raphael Köster; Kevin R. McKee; Richard Everett 001; Laura Weidinger; William S. Isaac; Edward Hughes 001; Edgar A. Duéñez-Guzmán; Thore Graepel; Matthew M. Botvinick; Joel Z. Leibo (CoRR, 2020)

DeepMind Lab2D. - Charles Beattie; Thomas Köppe; Edgar A. Duéñez-Guzmán; Joel Z. Leibo (CoRR, 2020)

Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot. - Joel Z. Leibo; Edgar A. Duéñez-Guzmán; Alexander Vezhnevets; John P. Agapiou; Peter Sunehag; Raphael Koster; Jayd Matyas; Charlie Beattie; Igor Mordatch; Thore Graepel (ICML, 2021)

A learning agent that acquires social norms from public sanctions in decentralized multi-agent settings. - Eugene Vinitsky; Raphael Köster; John P. Agapiou; Edgar A. Duéñez-Guzmán; Alexander Sasha Vezhnevets; Joel Z. Leibo (CoRR, 2021)

Statistical discrimination in learning agents. - 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 001; Karl Tuyls; Joel Z. Leibo (CoRR, 2021)

D3C: Reducing the Price of Anarchy in Multi-Agent Learning. - Ian Gemp; Kevin R. McKee; Richard Everett 001; Edgar A. Duéñez-Guzmán; Yoram Bachrach; David Balduzzi; Andrea Tacchetti (AAMAS, 2022)

Developing, evaluating and scaling learning agents in multi-agent environments. - Ian Gemp; Thomas W. Anthony 001; Yoram Bachrach; Avishkar Bhoopchand; Kalesha Bullard; Jerome T. Connor; Vibhavari Dasagi; Bart De Vylder; Edgar A. Duéñez-Guzmán; Romuald Elie; Richard Everett 001; Daniel Hennes; et al. (AI Commun., 2022)

Hidden Agenda: a Social Deduction Game with Diverse Learned Equilibria. - Kavya Kopparapu; Edgar A. Duéñez-Guzmán; Jayd Matyas; Alexander Sasha Vezhnevets; John P. Agapiou; Kevin R. McKee; Richard Everett 001; Janusz Marecki; Joel Z. Leibo; Thore Graepel (CoRR, 2022)

Melting Pot 2.0. - 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 Bradley Johanson; et al. (CoRR, 2022)

Diversity Through Exclusion (DTE): Niche Identification for Reinforcement Learning through Value-Decomposition. - Peter Sunehag; Alexander Sasha Vezhnevets; Edgar A. Duéñez-Guzmán; Igor Mordatch; Joel Z. Leibo (AAMAS, 2023)

Heterogeneous Social Value Orientation Leads to Meaningful Diversity in Sequential Social Dilemmas. - Udari Madhushani; Kevin R. McKee; John P. Agapiou; Joel Z. Leibo; Richard Everett 001; Thomas W. Anthony 001; Edward Hughes 001; Karl Tuyls; Edgar A. Duéñez-Guzmán (CoRR, 2023)

Doing the right thing for the right reason: Evaluating artificial moral cognition by probing cost insensitivity. - Yiran Mao; Madeline G. Reinecke; Markus Kunesch; Edgar A. Duéñez-Guzmán; Ramona Comanescu; Julia Haas; Joel Z. Leibo (CoRR, 2023)

Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia. - 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 (CoRR, 2023)

The Puzzle of Evaluating Moral Cognition in Artificial Agents. - Madeline G. Reinecke; Yiran Mao; Markus Kunesch; Edgar A. Duéñez-Guzmán; Julia Haas; Joel Z. Leibo (Cogn. Sci., 2023)

A social path to human-like artificial intelligence. - Edgar A. Duéñez-Guzmán; Suzanne Sadedin; Jane X. Wang; Kevin R. McKee; Joel Z. Leibo (Nat. Mac. Intell., 2023)

Approximating the Core via Iterative Coalition Sampling. - Ian Gemp; Marc Lanctot; Luke Marris; Yiran Mao; Edgar A. Duéñez-Guzmán; Sarah Perrin; András György 001; Romuald Elie; Georgios Piliouras; Michael Kaisers; Daniel Hennes; Kalesha Bullard; et al. (AAMAS, 2024)

Melting Pot Contest: Charting the Future of Generalized Cooperative Intelligence. - Rakshit Trivedi; Akbir Khan; Jesse Clifton; Lewis Hammond; Edgar A. Duéñez-Guzmán; Dipam Chakraborty; John P. Agapiou; Jayd Matyas; Alexander Sasha Vezhnevets; Barna Pásztor; Yunke Ao; Omar G. Younis; et al. (NeurIPS, 2024)

A theory of appropriateness with applications to generative artificial intelligence. - 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; et al. (CoRR, 2024)