Why The Brain Separates Face Recognition From Object Recognition. - Joel Z. Leibo; Jim Mutch; Tomaso A. Poggio (NIPS, 2011)

Learning and disrupting invariance in visual recognition with a temporal association rule. - Leyla Isik; Joel Z. Leibo; Tomaso A. Poggio (Frontiers Comput. Neurosci., 2012)

Learning invariant representations and applications to face verification. - Qianli Liao; Joel Z. Leibo; Tomaso A. Poggio (NIPS, 2013)

Unsupervised Learning of Invariant Representations in Hierarchical Architectures. - Fabio Anselmi; Joel Z. Leibo; Lorenzo Rosasco; Jim Mutch; Andrea Tacchetti; Tomaso A. Poggio (CoRR, 2013)

Can a biologically-plausible hierarchy effectively replace face detection, alignment, and recognition pipelines? - Qianli Liao; Joel Z. Leibo; Youssef Mroueh; Tomaso A. Poggio (CoRR, 2013)

Throwing Down the Visual Intelligence Gauntlet. - Cheston Tan; Joel Z. Leibo; Tomaso A. Poggio (Machine Learning for Computer Vision, 2013)

Subtasks of Unconstrained Face Recognition. - Joel Z. Leibo; Qianli Liao; Tomaso A. Poggio (VISAPP (2), 2014)

Unsupervised learning of clutter-resistant visual representations from natural videos. - Qianli Liao; Joel Z. Leibo; Tomaso A. Poggio (CoRR, 2014)

Approximate Hubel-Wiesel Modules and the Data Structures of Neural Computation. - Joel Z. Leibo; Julien Cornebise; Sergio Gómez; Demis Hassabis (CoRR, 2015)

The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex. - Joel Z. Leibo; Qianli Liao; Fabio Anselmi; Tomaso A. Poggio (PLoS Comput. Biol., 2015)

How Important Is Weight Symmetry in Backpropagation? - Qianli Liao; Joel Z. Leibo; Tomaso A. Poggio (AAAI, 2016)

Using Fast Weights to Attend to the Recent Past. - Jimmy Ba; Geoffrey E. Hinton; Volodymyr Mnih; Joel Z. Leibo; Catalin Ionescu (NIPS, 2016)

DeepMind Lab. - Charles Beattie; Joel Z. Leibo; Denis Teplyashin; Tom Ward; Marcus Wainwright; Heinrich Küttler; Andrew Lefrancq; Simon Green; Víctor Valdés; Amir Sadik; Julian Schrittwieser; Keith Anderson; et al. (CoRR, 2016)

Model-Free Episodic Control. - Charles Blundell; Benigno Uria; Alexander Pritzel; Yazhe Li; Avraham Ruderman; Joel Z. Leibo; Jack W. Rae; Daan Wierstra; Demis Hassabis (CoRR, 2016)

View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation. - Joel Z. Leibo; Qianli Liao; Winrich Freiwald; Fabio Anselmi; Tomaso A. Poggio (CoRR, 2016)

Unsupervised learning of invariant representations. - Fabio Anselmi; Joel Z. Leibo; Lorenzo Rosasco; Jim Mutch; Andrea Tacchetti; Tomaso A. Poggio (Theor. Comput. Sci., 2016)

Multi-agent Reinforcement Learning in Sequential Social Dilemmas. - Joel Z. Leibo; Vinícius Flores Zambaldi; Marc Lanctot; Janusz Marecki; Thore Graepel (AAMAS, 2017)

Learning to reinforcement learn. - Jane Wang 001; Zeb Kurth-Nelson; Hubert Soyer; Joel Z. Leibo; Dhruva Tirumala; Rémi Munos; Charles Blundell; Dharshan Kumaran; Matt M. Botvinick (CogSci, 2017)

Reinforcement Learning with Unsupervised Auxiliary Tasks. - Max Jaderberg; Volodymyr Mnih; Wojciech Marian Czarnecki; Tom Schaul; Joel Z. Leibo; David Silver; Koray Kavukcuoglu (ICLR, 2017)

A multi-agent reinforcement learning model of common-pool resource appropriation. - Julien Pérolat; Joel Z. Leibo; Vinícius Flores Zambaldi; Charles Beattie; Karl Tuyls; Thore Graepel (NIPS, 2017)

Learning from Demonstrations for Real World Reinforcement Learning. - Todd Hester; Matej Vecerík; Olivier Pietquin; Marc Lanctot; Tom Schaul; Bilal Piot; Andrew Sendonaris; Gabriel Dulac-Arnold; Ian Osband; John P. Agapiou; Joel Z. Leibo; Audrunas Gruslys (CoRR, 2017)

Value-Decomposition Networks For Cooperative Multi-Agent Learning. - Peter Sunehag; Guy Lever; Audrunas Gruslys; Wojciech Marian Czarnecki; Vinícius Flores Zambaldi; Max Jaderberg; Marc Lanctot; Nicolas Sonnerat; Joel Z. Leibo; Karl Tuyls; Thore Graepel (CoRR, 2017)

Symmetric Decomposition of Asymmetric Games. - Karl Tuyls; Julien Pérolat; Marc Lanctot; Georg Ostrovski; Rahul Savani; Joel Z. Leibo; Toby Ord; Thore Graepel; Shane Legg (CoRR, 2017)

Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017. - Matthew M. Botvinick; David G. T. Barrett; Peter W. Battaglia; Nando de Freitas; Dharshan Kumaran; Joel Z. Leibo; Tim Lillicrap; Joseph Modayil; S. Mohamed; Neil C. Rabinowitz; Danilo Jimenez Rezende; Adam Santoro; et al. (CoRR, 2017)

Deep Q-learning From Demonstrations. - Todd Hester; Matej Vecerík; Olivier Pietquin; Marc Lanctot; Tom Schaul; Bilal Piot; Dan Horgan; John Quan; Andrew Sendonaris; Ian Osband; Gabriel Dulac-Arnold; John P. Agapiou; et al. (AAAI, 2018)

Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward. - Peter Sunehag; Guy Lever; Audrunas Gruslys; Wojciech Marian Czarnecki; Vinícius Flores Zambaldi; Max Jaderberg; Marc Lanctot; Nicolas Sonnerat; Joel Z. Leibo; Karl Tuyls; Thore Graepel (AAMAS, 2018)

A Generalised Method for Empirical Game Theoretic Analysis. - Karl Tuyls; Julien Pérolat; Marc Lanctot; Joel Z. Leibo; Thore Graepel (AAMAS, 2018)

Emergent Communication through Negotiation. - Kris Cao; Angeliki Lazaridou; Marc Lanctot; Joel Z. Leibo; Karl Tuyls; Stephen Clark (ICLR (Poster), 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)

Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents. - Joel Z. Leibo; Cyprien de Masson d'Autume; Daniel Zoran; David Amos; Charles Beattie; Keith Anderson; Antonio García Castañeda; Manuel Sanchez; Simon Green; Audrunas Gruslys; Shane Legg; Demis Hassabis; et al. (CoRR, 2018)

Kickstarting Deep Reinforcement Learning. - Simon Schmitt; Jonathan J. Hudson; Augustin Zídek; Simon Osindero; Carl Doersch; Wojciech M. Czarnecki; Joel Z. Leibo; Heinrich Küttler; Andrew Zisserman; Karen Simonyan; S. M. Ali Eslami (CoRR, 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)

Unsupervised Predictive Memory in a Goal-Directed Agent. - Greg Wayne; Chia-Chun Hung; David Amos; Mehdi Mirza; Arun Ahuja; Agnieszka Grabska-Barwinska; Jack W. Rae; Piotr Mirowski; Joel Z. Leibo; Adam Santoro; Mevlana Gemici; Malcolm Reynolds; et al. (CoRR, 2018)

Human-level performance in first-person multiplayer games with population-based deep reinforcement learning. - Max Jaderberg; Wojciech M. Czarnecki; Iain Dunning; Luke Marris; Guy Lever; Antonio García Castañeda; Charles Beattie; Neil C. Rabinowitz; Ari S. Morcos; Avraham Ruderman; Nicolas Sonnerat; Tim Green; et al. (CoRR, 2018)

Intrinsic Social Motivation via Causal Influence in Multi-Agent RL. - Natasha Jaques; Angeliki Lazaridou; Edward Hughes 001; Çaglar Gülçehre; Pedro A. Ortega; DJ Strouse; Joel Z. Leibo; Nando de Freitas (CoRR, 2018)

The Imitation Game: Learned Reciprocity in Markov games. - Tom Eccles; Edward Hughes 001; János Kramár; Steven Wheelwright; Joel Z. Leibo (AAMAS, 2019)

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)

Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning. - Natasha Jaques; Angeliki Lazaridou; Edward Hughes 001; Çaglar Gülçehre; Pedro A. Ortega; DJ Strouse; Joel Z. Leibo; Nando de Freitas (ICML, 2019)

Reinforcement Learning Agents acquire Flocking and Symbiotic Behaviour in Simulated Ecosystems. - Peter Sunehag; Guy Lever; Siqi Liu 002; Josh Merel; Nicolas Heess; Joel Z. Leibo; Edward Hughes 001; Tom Eccles; Thore Graepel (ALIFE, 2019)

Interval timing in deep reinforcement learning agents. - Ben Deverett; Ryan Faulkner 001; Meire Fortunato; Gregory Wayne; Joel Z. Leibo (NeurIPS, 2019)

Generalization of Reinforcement Learners with Working and Episodic Memory. - Meire Fortunato; Melissa Tan; Ryan Faulkner 001; Steven Hansen 001; Adrià Puigdomènech Badia; Gavin Buttimore; Charlie Deck; Joel Z. Leibo; Charles Blundell (NeurIPS, 2019)

Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research. - Joel Z. Leibo; Edward Hughes 001; Marc Lanctot; Thore Graepel (CoRR, 2019)

Learning Reciprocity in Complex Sequential Social Dilemmas. - Tom Eccles; Edward Hughes 001; János Kramár; Steven Wheelwright; Joel Z. Leibo (CoRR, 2019)

Options as responses: Grounding behavioural hierarchies in multi-agent RL. - Alexander Sasha Vezhnevets; Yuhuai Wu; Rémi Leblond; Joel Z. Leibo (CoRR, 2019)

Toward high-performance, memory-efficient, and fast reinforcement learning - Lessons from decision neuroscience. - Ben Seymour; Joel Z. Leibo; Su Jin An; Sang Wan Lee (Sci. Robotics, 2019)

Learning to Resolve Alliance Dilemmas in Many-Player Zero-Sum Games. - Edward Hughes 001; Thomas W. Anthony 001; Tom Eccles; Joel Z. Leibo; David Balduzzi; Yoram Bachrach (AAMAS, 2020)

Silly Rules Improve the Capacity of Agents to Learn Stable Enforcement and Compliance Behaviors. - Raphael Koster; Dylan Hadfield-Menell; Gillian K. Hadfield; Joel Z. Leibo (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)

Smooth markets: A basic mechanism for organizing gradient-based learners. - David Balduzzi; Wojciech M. Czarnecki; Tom Anthony 001; Ian Gemp; Edward Hughes 001; Joel Z. Leibo; Georgios Piliouras; Thore Graepel (ICLR, 2020)

OPtions as REsponses: Grounding behavioural hierarchies in multi-agent reinforcement learning. - Alexander Vezhnevets; Yuhuai Wu; Maria K. Eckstein; Rémi Leblond; Joel Z. Leibo (ICML, 2020)

Bounds and dynamics for empirical game theoretic analysis. - Karl Tuyls; Julien Pérolat; Marc Lanctot; Edward Hughes 001; Richard Everett 001; Joel Z. Leibo; Csaba Szepesvári; Thore Graepel (Auton. Agents Multi Agent Syst., 2020)

Negotiating team formation using deep reinforcement learning. - Yoram Bachrach; Richard Everett 001; Edward Hughes 001; Angeliki Lazaridou; Joel Z. Leibo; Marc Lanctot; Michael Johanson; Wojciech M. Czarnecki; Thore Graepel (Artif. Intell., 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)

Open Problems in Cooperative AI. - Allan Dafoe; Edward Hughes 001; Yoram Bachrach; Tantum Collins; Kevin R. McKee; Joel Z. Leibo; Kate Larson; Thore Graepel (CoRR, 2020)

Modelling Cooperation in Network Games with Spatio-Temporal Complexity. - Michiel A. Bakker; Richard Everett 001; Laura Weidinger; Iason Gabriel; William S. Isaac; Joel Z. Leibo; Edward Hughes 001 (AAMAS, 2021)

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)

Quantifying environment and population diversity in multi-agent reinforcement learning. - Kevin R. McKee; Joel Z. Leibo; Charlie Beattie; Richard Everett 001 (CoRR, 2021)

Deep reinforcement learning models the emergent dynamics of human cooperation. - Kevin R. McKee; Edward Hughes 001; Tina O. Zhu; Martin J. Chadwick; Raphael Koster; Antonio García Castañeda; Charlie Beattie; Thore Graepel; Matthew M. Botvinick; Joel Z. Leibo (CoRR, 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)

Quantifying the effects of environment and population diversity in multi-agent reinforcement learning. - Kevin R. McKee; Joel Z. Leibo; Charlie Beattie; Richard Everett 001 (Auton. Agents Multi Agent Syst., 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)

Emergent Bartering Behaviour in Multi-Agent Reinforcement Learning. - Michael Bradley Johanson; Edward Hughes 001; Finbarr Timbers; Joel Z. Leibo (CoRR, 2022)

The emergence of division of labor through decentralized social sanctioning. - Anil Yaman; Joel Z. Leibo; Giovanni Iacca; Sang Wan Lee (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)

Importance of prefrontal meta control in human-like reinforcement learning. - Jee Hang Lee; Joel Z. Leibo; Su Jin An; Sang Wan Lee (Frontiers Comput. Neurosci., 2022)

Meta-control of social learning strategies. - Anil Yaman; Nicolas Bredèche; Onur Çaylak; Joel Z. Leibo; Sang Wan Lee (PLoS Comput. Biol., 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)

Framework-Based Qualitative Analysis of Free Responses of Large Language Models: Algorithmic Fidelity. - Aliya Amirova; Theodora Fteropoulli; Nafiso Ahmed; Martin R. Cowie; Joel Z. Leibo (CoRR, 2023)

Machine Culture. - Levin Brinkmann; Fabian Baumann; Jean-François Bonnefon; Maxime Derex; Thomas F. Müller; Anne-Marie Nussberger; Agnieszka Czaplicka; Alberto Acerbi; Thomas L. Griffiths 001; Joseph Henrich; Joel Z. Leibo; Richard McElreath; et al. (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)

A Review of Cooperation in Multi-agent Learning. - Yali Du 001; Joel Z. Leibo; Usman Islam; Richard Willis; Peter Sunehag (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)

Neural Population Learning beyond Symmetric Zero-Sum Games. - Siqi Liu 002; Luke Marris; Marc Lanctot; Georgios Piliouras; Joel Z. Leibo; Nicolas Heess (AAMAS, 2024)

Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning. - Jonathan Cook 004; Chris Lu 001; Edward Hughes 001; Joel Z. Leibo; Jakob N. Foerster (NeurIPS, 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)

Visualizing 2x2 Normal-Form Games: twoxtwogame LaTeX Package. - Luke Marris; Ian Gemp; Siqi Liu 002; Joel Z. Leibo; Georgios Piliouras (CoRR, 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)

Resolving social dilemmas with minimal reward transfer. - Richard Willis; Yali Du 001; Joel Z. Leibo; Michael Luck (Auton. Agents Multi Agent Syst., 2024)

InvestESG: A multi-agent reinforcement learning benchmark for studying climate investment as a social dilemma. - Xiaoxuan Hou; Jiayi Yuan 002; Joel Z. Leibo; Natasha Jaques (ICLR, 2025)

Will Systems of LLM Agents Lead to Cooperation: An Investigation into a Social Dilemma. - Richard Willis; Yali Du 001; Joel Z. Leibo (AAMAS, 2025)

Resolving Social Dilemmas with Minimal Reward Transfer - Extended Abstract. - Richard Willis; Yali Du 001; Joel Z. Leibo; Michael Luck (AAMAS, 2025)

Quantifying the Self-Interest Level of Markov Social Dilemmas. - Richard Willis; Yali Du 001; Joel Z. Leibo; Michael Luck (CoRR, 2025)

Will Systems of LLM Agents Cooperate: An Investigation into a Social Dilemma. - Richard Willis; Yali Du 001; Joel Z. Leibo; Michael Luck (CoRR, 2025)

Simulation Streams: A Programming Paradigm for Controlling Large Language Models and Building Complex Systems with Generative AI. - Peter Sunehag; Joel Z. Leibo (CoRR, 2025)

Multi-Agent Risks from Advanced AI. - Lewis Hammond; Alan Chan; Jesse Clifton; Jason Hoelscher-Obermaier; Akbir Khan; Euan McLean; Chandler Smith; Wolfram Barfuss; Jakob N. Foerster; Tomas Gavenciak; The Anh Han; Edward Hughes 001; et al. (CoRR, 2025)

SocialJax: An Evaluation Suite for Multi-agent Reinforcement Learning in Sequential Social Dilemmas. - Zihao Guo; Richard Willis; Shuqing Shi; Tristan Tomilin; Joel Z. Leibo; Yali Du 001 (CoRR, 2025)

Societal and technological progress as sewing an ever-growing, ever-changing, patchy, and polychrome quilt. - Joel Z. Leibo; Alexander Sasha Vezhnevets; William A. Cunningham; Sébastien Krier; Manfred Diaz; Simon Osindero (CoRR, 2025)

Meaning Is Not A Metric: Using LLMs to make cultural context legible at scale. - Cody Kommers; Drew Hemment; Maria Antoniak; Joel Z. Leibo; Hoyt Long; Emily Robinson; Adam Sobey (CoRR, 2025)

Using Large Language Models to Simulate Human Behavioural Experiments: Port of Mars. - Oliver Slumbers; Joel Z. Leibo; Marco A. Janssen (CoRR, 2025)

Modeling human reputation-seeking behavior in a spatio-temporally complex public good provision game. - Edward Hughes 001; Tina O. Zhu; Martin J. Chadwick; Raphael Koster; Antonio García Castañeda; Charles Beattie; Thore Graepel; Matthew M. Botvinick; Joel Z. Leibo (CoRR, 2025)

Multi-Actor Generative Artificial Intelligence as a Game Engine. - Alexander Sasha Vezhnevets; Jayd Matyas; Logan Cross; Davide Paglieri; Minsuk Chang; William A. Cunningham; Simon Osindero; William S. Isaac; Joel Z. Leibo (CoRR, 2025)