Joel Z. Leibo - RankMe

136 papers A* 13A 14B 2C 1Journal 98Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Generative Model of Conspicuous Consumption and Status Signaling. CoRR Logan Cross, Jordi Grau-Moya, William A. Cunningham, Alexander Sasha Vezhnevets, Joel Z. Leibo
2026	J	`jnl`	A Theory of Appropriateness That Accounts for Norms of Rationality. CoRR Joel Z. Leibo, Alexander Sasha Vezhnevets, Manfred Diaz, John P. Agapiou, William A. Cunningham, Peter Sunehag, Logan Cross, Raphael Koster, Stanley M. Bileschi, Minsuk Chang, Iyad Rahwan, Simon Osindero, James A. Evans
2026	J	`jnl`	Evaluating Collective Behaviour of Hundreds of LLM Agents. CoRR Richard Willis, Jianing Zhao, Yali Du, Joel Z. Leibo
2026	J	`jnl`	Generative AI collective behavior needs an interactionist paradigm. CoRR Laura Ferrarotti, Gian Maria Campedelli, Roberto Dessì, Andrea Baronchelli, Giovanni Iacca, Kathleen M. Carley, Alex Pentland, Joel Z. Leibo, James Evans, Bruno Lepri
2026	J	`jnl`	How LLMs Distort Our Written Language. CoRR Marwa Abdulhai, Isadora White, Yanming Wan, Ibrahim Qureshi, Joel Z. Leibo, Max Kleiman-Weiner, Natasha Jaques
2026	J	`jnl`	Persona Generators: Generating Diverse Synthetic Personas at Scale. CoRR Davide Paglieri, Logan Cross, William A. Cunningham, Joel Z. Leibo, Alexander Sasha Vezhnevets
2026	J	`jnl`	Social physics in the age of artificial intelligence. CoRR The Anh Han, Joel Z. Leibo, Tom Griffiths, Iyad Rahwan, Fernando Santos, Matjaz Perc, Valerio Capraro
2025	J	`jnl`	A Pragmatic View of AI Personhood. CoRR Joel Z. Leibo, Alexander Sasha Vezhnevets, William A. Cunningham, Stanley M. Bileschi
2025	J	`jnl`	Beyond the high score: Prosocial ability profiles of multi-agent populations. CoRR Marko Tesic, Yue Zhao, Joel Z. Leibo, Rakshit S. Trivedi, José Hernández-Orallo
2025	J	`jnl`	Evaluating Generalization Capabilities of LLM-Based Agents in Mixed-Motive Scenarios Using Concordia. CoRR Chandler Smith, Marwa Abdulhai, Manfred Diaz, Marko Tesic, Rakshit S. Trivedi, Alexander Sasha Vezhnevets, Lewis Hammond, Jesse Clifton, Minsuk Chang, Edgar A. Duéñez-Guzmán, John P. Agapiou, Jayd Matyas, Danny Karmon, Dylan Hadfield-Menell, Natasha Jaques, Tim Baarslag, José Hernández-Orallo, Joel Z. Leibo
2025	B	`conf`	I Know I Should: Normative Competence From Biology To AI. CogSci Joel Z. Leibo, Sydney Levine, John Michael, Jordan Theriault, Luca Tummolini
2025	A*	`conf`	InvestESG: A multi-agent reinforcement learning benchmark for studying climate investment as a social dilemma. ICLR Xiaoxuan Hou, Jiayi Yuan, Joel Z. Leibo, Natasha Jaques
2025	J	`jnl`	Meaning Is Not A Metric: Using LLMs to make cultural context legible at scale. CoRR Cody Kommers, Drew Hemment, Maria Antoniak, Joel Z. Leibo, Hoyt Long, Emily Robinson, Adam Sobey
2025	J	`jnl`	Modeling human reputation-seeking behavior in a spatio-temporally complex public good provision game. CoRR Edward Hughes, Tina O. Zhu, Martin J. Chadwick, Raphael Koster, Antonio García Castañeda, Charles Beattie, Thore Graepel, Matthew M. Botvinick, Joel Z. Leibo
2025	J	`jnl`	Multi-Actor Generative Artificial Intelligence as a Game Engine. CoRR Alexander Sasha Vezhnevets, Jayd Matyas, Logan Cross, Davide Paglieri, Minsuk Chang, William A. Cunningham, Simon Osindero, William S. Isaac, Joel Z. Leibo
2025	J	`jnl`	Multi-Agent Risks from Advanced AI. CoRR 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, Vojtech Kovarík, Jan Kulveit, Joel Z. Leibo, Caspar Oesterheld, Christian Schröder de Witt, Nisarg Shah, Michael P. Wellman, Paolo Bova, Theodor Cimpeanu, Carson Ezell, Quentin Feuillade-Montixi, Matija Franklin, Esben Kran, Igor Krawczuk, Max Lamparth, Niklas Lauffer, Alexander Meinke, Sumeet Motwani, Anka Reuel, Vincent Conitzer, Michael Dennis, Iason Gabriel, Adam Gleave, Gillian K. Hadfield, Nika Haghtalab, Atoosa Kasirzadeh, Sébastien Krier, Kate Larson, Joel Lehman, David C. Parkes, Georgios Piliouras, Iyad Rahwan
2025	A*	`conf`	Quantifying the Self-Interest Level of Markov Social Dilemmas. IJCAI Richard Willis, Yali Du, Joel Z. Leibo, Michael Luck
2025	J	`jnl`	Quantifying the Self-Interest Level of Markov Social Dilemmas. CoRR Richard Willis, Yali Du, Joel Z. Leibo, Michael Luck
2025	A	`conf`	Resolving Social Dilemmas with Minimal Reward Transfer - Extended Abstract. AAMAS Richard Willis, Yali Du, Joel Z. Leibo, Michael Luck
2025	J	`jnl`	Simulation Streams: A Programming Paradigm for Controlling Large Language Models and Building Complex Systems with Generative AI. CoRR Peter Sunehag, Joel Z. Leibo
2025	J	`jnl`	SocialJax: An Evaluation Suite for Multi-agent Reinforcement Learning in Sequential Social Dilemmas. CoRR Zihao Guo, Richard Willis, Shuqing Shi, Tristan Tomilin, Joel Z. Leibo, Yali Du
2025	J	`jnl`	Societal and technological progress as sewing an ever-growing, ever-changing, patchy, and polychrome quilt. CoRR Joel Z. Leibo, Alexander Sasha Vezhnevets, William A. Cunningham, Sébastien Krier, Manfred Diaz, Simon Osindero
2025	J	`jnl`	Using Large Language Models to Simulate Human Behavioural Experiments: Port of Mars. CoRR Oliver Slumbers, Joel Z. Leibo, Marco A. Janssen
2025	J	`jnl`	Virtual Agent Economies. CoRR Nenad Tomasev, Matija Franklin, Joel Z. Leibo, Julian Jacobs, William A. Cunningham, Iason Gabriel, Simon Osindero
2025	J	`jnl`	Will Systems of LLM Agents Cooperate: An Investigation into a Social Dilemma. CoRR Richard Willis, Yali Du, Joel Z. Leibo, Michael Luck
2025	A	`conf`	Will Systems of LLM Agents Lead to Cooperation: An Investigation into a Social Dilemma. AAMAS Richard Willis, Yali Du, Joel Z. Leibo
2024	J	`jnl`	A social path to human-like artificial intelligence. CoRR Edgar A. Duéñez-Guzmán, Suzanne Sadedin, Jane X. Wang, Kevin R. McKee, Joel Z. Leibo
2024	J	`jnl`	A theory of appropriateness with applications to generative artificial intelligence. CoRR 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
2024	A*	`conf`	Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning. NeurIPS Jonathan Cook, Chris Lu, Edward Hughes, Joel Z. Leibo, Jakob N. Foerster
2024	J	`jnl`	Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning. CoRR Jonathan Cook, Chris Lu, Edward Hughes, Joel Z. Leibo, Jakob N. Foerster
2024	J	`jnl`	InvestESG: A multi-agent reinforcement learning benchmark for studying climate investment as a social dilemma. CoRR Xiaoxuan Hou, Jiayi Yuan, Joel Z. Leibo, Natasha Jaques
2024	A*	`conf`	Melting Pot Contest: Charting the Future of Generalized Cooperative Intelligence. NeurIPS Rakshit S. 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, Jiawei Huang, Benjamin Swain, Haoyuan Qin, Mian Deng, Ziwei Deng, Utku Erdoganaras, Yue Zhao, Marko Tesic, Natasha Jaques, Jakob N. Foerster, Vincent Conitzer, José Hernández-Orallo, Dylan Hadfield-Menell, Joel Z. Leibo
2024	A	`conf`	Neural Population Learning beyond Symmetric Zero-Sum Games. AAMAS Siqi Liu, Luke Marris, Marc Lanctot, Georgios Piliouras, Joel Z. Leibo, Nicolas Heess
2024	J	`jnl`	Neural Population Learning beyond Symmetric Zero-sum Games. CoRR Siqi Liu, Luke Marris, Marc Lanctot, Georgios Piliouras, Joel Z. Leibo, Nicolas Heess
2024	J	`jnl`	Resolving social dilemmas with minimal reward transfer. Auton. Agents Multi Agent Syst. Richard Willis, Yali Du, Joel Z. Leibo, Michael Luck
2024	J	`jnl`	Visualizing 2x2 Normal-Form Games: twoxtwogame LaTeX Package. CoRR Luke Marris, Ian Gemp, Siqi Liu, Joel Z. Leibo, Georgios Piliouras
2023	J	`jnl`	A Review of Cooperation in Multi-agent Learning. CoRR Yali Du, Joel Z. Leibo, Usman Islam, Richard Willis, Peter Sunehag
2023	J	`jnl`	A social path to human-like artificial intelligence. Nat. Mac. Intell. Edgar A. Duéñez-Guzmán, Suzanne Sadedin, Jane X. Wang, Kevin R. McKee, Joel Z. Leibo
2023	A	`conf`	Diversity Through Exclusion (DTE): Niche Identification for Reinforcement Learning through Value-Decomposition. AAMAS Peter Sunehag, Alexander Sasha Vezhnevets, Edgar A. Duéñez-Guzmán, Igor Mordatch, Joel Z. Leibo
2023	J	`jnl`	Diversity Through Exclusion (DTE): Niche Identification for Reinforcement Learning through Value-Decomposition. CoRR Peter Sunehag, Alexander Sasha Vezhnevets, Edgar A. Duéñez-Guzmán, Igor Mordatch, Joel Z. Leibo
2023	J	`jnl`	Doing the right thing for the right reason: Evaluating artificial moral cognition by probing cost insensitivity. CoRR Yiran Mao, Madeline G. Reinecke, Markus Kunesch, Edgar A. Duéñez-Guzmán, Ramona Comanescu, Julia Haas, Joel Z. Leibo
2023	J	`jnl`	Framework-Based Qualitative Analysis of Free Responses of Large Language Models: Algorithmic Fidelity. CoRR Aliya Amirova, Theodora Fteropoulli, Nafiso Ahmed, Martin R. Cowie, Joel Z. Leibo
2023	J	`jnl`	Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia. CoRR 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
2023	J	`jnl`	Heterogeneous Social Value Orientation Leads to Meaningful Diversity in Sequential Social Dilemmas. CoRR Udari Madhushani, Kevin R. McKee, John P. Agapiou, Joel Z. Leibo, Richard Everett, Thomas W. Anthony, Edward Hughes, Karl Tuyls, Edgar A. Duéñez-Guzmán
2023	J	`jnl`	Machine Culture. CoRR Levin Brinkmann, Fabian Baumann, Jean-François Bonnefon, Maxime Derex, Thomas F. Müller, Anne-Marie Nussberger, Agnieszka Czaplicka, Alberto Acerbi, Thomas L. Griffiths, Joseph Henrich, Joel Z. Leibo, Richard McElreath, Pierre-Yves Oudeyer, Jonathan Stray, Iyad Rahwan
2023	J	`jnl`	Resolving social dilemmas with minimal reward transfer. CoRR Richard Willis, Yali Du, Joel Z. Leibo, Michael Luck
2023	J	`jnl`	The Puzzle of Evaluating Moral Cognition in Artificial Agents. Cogn. Sci. Madeline G. Reinecke, Yiran Mao, Markus Kunesch, Edgar A. Duéñez-Guzmán, Julia Haas, Joel Z. Leibo
2022	J	`jnl`	Emergent Bartering Behaviour in Multi-Agent Reinforcement Learning. CoRR Michael Bradley Johanson, Edward Hughes, Finbarr Timbers, Joel Z. Leibo
2022	J	`jnl`	Hidden Agenda: a Social Deduction Game with Diverse Learned Equilibria. CoRR 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
2022	J	`jnl`	Importance of prefrontal meta control in human-like reinforcement learning. Frontiers Comput. Neurosci. Jee Hang Lee, Joel Z. Leibo, Su Jin An, Sang Wan Lee
2022	J	`jnl`	Melting Pot 2.0. CoRR 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, Sukhdeep Singh, Julia Haas, Igor Mordatch, Dean Mobbs, Joel Z. Leibo
2022	J	`jnl`	Meta-control of social learning strategies. PLoS Comput. Biol. Anil Yaman, Nicolas Bredèche, Onur Çaylak, Joel Z. Leibo, Sang Wan Lee
2022	J	`jnl`	Quantifying the effects of environment and population diversity in multi-agent reinforcement learning. Auton. Agents Multi Agent Syst. Kevin R. McKee, Joel Z. Leibo, Charlie Beattie, Richard Everett
2022	J	`jnl`	The emergence of division of labor through decentralized social sanctioning. CoRR Anil Yaman, Joel Z. Leibo, Giovanni Iacca, Sang Wan Lee
2021	J	`jnl`	A learning agent that acquires social norms from public sanctions in decentralized multi-agent settings. CoRR Eugene Vinitsky, Raphael Köster, John P. Agapiou, Edgar A. Duéñez-Guzmán, Alexander Sasha Vezhnevets, Joel Z. Leibo
2021	J	`jnl`	Deep reinforcement learning models the emergent dynamics of human cooperation. CoRR Kevin R. McKee, Edward Hughes, Tina O. Zhu, Martin J. Chadwick, Raphael Koster, Antonio García Castañeda, Charlie Beattie, Thore Graepel, Matthew M. Botvinick, Joel Z. Leibo
2021	J	`jnl`	Meta-control of social learning strategies. CoRR Anil Yaman, Nicolas Bredèche, Onur Çaylak, Joel Z. Leibo, Sang Wan Lee
2021	A	`conf`	Modelling Cooperation in Network Games with Spatio-Temporal Complexity. AAMAS Michiel A. Bakker, Richard Everett, Laura Weidinger, Iason Gabriel, William S. Isaac, Joel Z. Leibo, Edward Hughes
2021	J	`jnl`	Modelling Cooperation in Network Games with Spatio-Temporal Complexity. CoRR Michiel A. Bakker, Richard Everett, Laura Weidinger, Iason Gabriel, William S. Isaac, Joel Z. Leibo, Edward Hughes
2021	J	`jnl`	Quantifying environment and population diversity in multi-agent reinforcement learning. CoRR Kevin R. McKee, Joel Z. Leibo, Charlie Beattie, Richard Everett
2021	A*	`conf`	Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot. ICML Joel Z. Leibo, Edgar A. Duéñez-Guzmán, Alexander Vezhnevets, John P. Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charlie Beattie, Igor Mordatch, Thore Graepel
2021	J	`jnl`	Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot. CoRR Joel Z. Leibo, Edgar A. Duéñez-Guzmán, Alexander Sasha Vezhnevets, John P. Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charles Beattie, Igor Mordatch, Thore Graepel
2021	J	`jnl`	Statistical discrimination in learning agents. CoRR 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
2020	J	`jnl`	Bounds and dynamics for empirical game theoretic analysis. Auton. Agents Multi Agent Syst. Karl Tuyls, Julien Pérolat, Marc Lanctot, Edward Hughes, Richard Everett, Joel Z. Leibo, Csaba Szepesvári, Thore Graepel
2020	J	`jnl`	DeepMind Lab2D. CoRR Charles Beattie, Thomas Köppe, Edgar A. Duéñez-Guzmán, Joel Z. Leibo
2020	A	`conf`	Learning to Resolve Alliance Dilemmas in Many-Player Zero-Sum Games. AAMAS Edward Hughes, Thomas W. Anthony, Tom Eccles, Joel Z. Leibo, David Balduzzi, Yoram Bachrach
2020	J	`jnl`	Learning to Resolve Alliance Dilemmas in Many-Player Zero-Sum Games. CoRR Edward Hughes, Thomas W. Anthony, Tom Eccles, Joel Z. Leibo, David Balduzzi, Yoram Bachrach
2020	J	`jnl`	Model-free conventions in multi-agent reinforcement learning with heterogeneous preferences. CoRR Raphael Köster, Kevin R. McKee, Richard Everett, Laura Weidinger, William S. Isaac, Edward Hughes, Edgar A. Duéñez-Guzmán, Thore Graepel, Matthew M. Botvinick, Joel Z. Leibo
2020	J	`jnl`	Negotiating Team Formation Using Deep Reinforcement Learning. CoRR Yoram Bachrach, Richard Everett, Edward Hughes, Angeliki Lazaridou, Joel Z. Leibo, Marc Lanctot, Michael Johanson, Wojciech M. Czarnecki, Thore Graepel
2020	J	`jnl`	Negotiating team formation using deep reinforcement learning. Artif. Intell. Yoram Bachrach, Richard Everett, Edward Hughes, Angeliki Lazaridou, Joel Z. Leibo, Marc Lanctot, Michael Johanson, Wojciech M. Czarnecki, Thore Graepel
2020	A*	`conf`	OPtions as REsponses: Grounding behavioural hierarchies in multi-agent reinforcement learning. ICML Alexander Vezhnevets, Yuhuai Wu, Maria K. Eckstein, Rémi Leblond, Joel Z. Leibo
2020	J	`jnl`	Open Problems in Cooperative AI. CoRR Allan Dafoe, Edward Hughes, Yoram Bachrach, Tantum Collins, Kevin R. McKee, Joel Z. Leibo, Kate Larson, Thore Graepel
2020	A	`conf`	Silly Rules Improve the Capacity of Agents to Learn Stable Enforcement and Compliance Behaviors. AAMAS Raphael Koster, Dylan Hadfield-Menell, Gillian K. Hadfield, Joel Z. Leibo
2020	J	`jnl`	Silly rules improve the capacity of agents to learn stable enforcement and compliance behaviors. CoRR Raphael Köster, Dylan Hadfield-Menell, Gillian K. Hadfield, Joel Z. Leibo
2020	A*	`conf`	Smooth markets: A basic mechanism for organizing gradient-based learners. ICLR David Balduzzi, Wojciech M. Czarnecki, Tom Anthony, Ian Gemp, Edward Hughes, Joel Z. Leibo, Georgios Piliouras, Thore Graepel
2020	J	`jnl`	Smooth markets: A basic mechanism for organizing gradient-based learners. CoRR David Balduzzi, Wojciech M. Czarnecki, Thomas W. Anthony, Ian M. Gemp, Edward Hughes, Joel Z. Leibo, Georgios Piliouras, Thore Graepel
2020	A	`conf`	Social Diversity and Social Preferences in Mixed-Motive Reinforcement Learning. AAMAS Kevin R. McKee, Ian Gemp, Brian McWilliams, Edgar A. Duéñez-Guzmán, Edward Hughes, Joel Z. Leibo
2020	J	`jnl`	Social Diversity and Social Preferences in Mixed-Motive Reinforcement Learning. CoRR Kevin R. McKee, Ian Gemp, Brian McWilliams, Edgar A. Duéñez-Guzmán, Edward Hughes, Joel Z. Leibo
2019	J	`jnl`	Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research. CoRR Joel Z. Leibo, Edward Hughes, Marc Lanctot, Thore Graepel
2019	A	`conf`	Evolving Intrinsic Motivations for Altruistic Behavior. AAMAS Jane X. Wang, Edward Hughes, Chrisantha Fernando, Wojciech M. Czarnecki, Edgar A. Duéñez-Guzmán, Joel Z. Leibo
2019	A*	`conf`	Generalization of Reinforcement Learners with Working and Episodic Memory. NeurIPS Meire Fortunato, Melissa Tan, Ryan Faulkner, Steven Hansen, Adrià Puigdomènech Badia, Gavin Buttimore, Charlie Deck, Joel Z. Leibo, Charles Blundell
2019	J	`jnl`	Generalization of Reinforcement Learners with Working and Episodic Memory. CoRR Meire Fortunato, Melissa Tan, Ryan Faulkner, Steven Hansen, Adrià Puigdomènech Badia, Gavin Buttimore, Charlie Deck, Joel Z. Leibo, Charles Blundell
2019	A*	`conf`	Interval timing in deep reinforcement learning agents. NeurIPS Ben Deverett, Ryan Faulkner, Meire Fortunato, Gregory Wayne, Joel Z. Leibo
2019	J	`jnl`	Interval timing in deep reinforcement learning agents. CoRR Ben Deverett, Ryan Faulkner, Meire Fortunato, Greg Wayne, Joel Z. Leibo
2019	J	`jnl`	Learning Reciprocity in Complex Sequential Social Dilemmas. CoRR Tom Eccles, Edward Hughes, János Kramár, Steven Wheelwright, Joel Z. Leibo
2019	A	`conf`	Malthusian Reinforcement Learning. AAMAS Joel Z. Leibo, Julien Pérolat, Edward Hughes, Steven Wheelwright, Adam H. Marblestone, Edgar A. Duéñez-Guzmán, Peter Sunehag, Iain Dunning, Thore Graepel
2019	J	`jnl`	Options as responses: Grounding behavioural hierarchies in multi-agent RL. CoRR Alexander Sasha Vezhnevets, Yuhuai Wu, Rémi Leblond, Joel Z. Leibo
2019	C	`conf`	Reinforcement Learning Agents acquire Flocking and Symbiotic Behaviour in Simulated Ecosystems. ALIFE Peter Sunehag, Guy Lever, Siqi Liu, Josh Merel, Nicolas Heess, Joel Z. Leibo, Edward Hughes, Tom Eccles, Thore Graepel
2019	A*	`conf`	Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning. ICML Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Çaglar Gülçehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, Nando de Freitas
2019	A	`conf`	The Imitation Game: Learned Reciprocity in Markov games. AAMAS Tom Eccles, Edward Hughes, János Kramár, Steven Wheelwright, Joel Z. Leibo
2019	J	`jnl`	Toward high-performance, memory-efficient, and fast reinforcement learning - Lessons from decision neuroscience. Sci. Robotics Ben Seymour, Joel Z. Leibo, Su Jin An, Sang Wan Lee
2018	A	`conf`	A Generalised Method for Empirical Game Theoretic Analysis. AAMAS Karl Tuyls, Julien Pérolat, Marc Lanctot, Joel Z. Leibo, Thore Graepel
2018	J	`jnl`	A Generalised Method for Empirical Game Theoretic Analysis. CoRR Karl Tuyls, Julien Pérolat, Marc Lanctot, Joel Z. Leibo, Thore Graepel
2018	A*	`conf`	Deep Q-learning From Demonstrations. AAAI 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, Joel Z. Leibo, Audrunas Gruslys
2018	—	`conf`	Emergent Communication through Negotiation. ICLR (Poster) Kris Cao, Angeliki Lazaridou, Marc Lanctot, Joel Z. Leibo, Karl Tuyls, Stephen Clark
2018	J	`jnl`	Emergent Communication through Negotiation. CoRR Kris Cao, Angeliki Lazaridou, Marc Lanctot, Joel Z. Leibo, Karl Tuyls, Stephen Clark
2018	J	`jnl`	Evolving intrinsic motivations for altruistic behavior. CoRR Jane X. Wang, Edward Hughes, Chrisantha Fernando, Wojciech M. Czarnecki, Edgar A. Duéñez-Guzmán, Joel Z. Leibo
2018	J	`jnl`	Human-level performance in first-person multiplayer games with population-based deep reinforcement learning. CoRR 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, Louise Deason, Joel Z. Leibo, David Silver, Demis Hassabis, Koray Kavukcuoglu, Thore Graepel
2018	A*	`conf`	Inequity aversion improves cooperation in intertemporal social dilemmas. NeurIPS Edward Hughes, 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
2018	J	`jnl`	Inequity aversion resolves intertemporal social dilemmas. CoRR Edward Hughes, 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
2018	J	`jnl`	Intrinsic Social Motivation via Causal Influence in Multi-Agent RL. CoRR Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Çaglar Gülçehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, Nando de Freitas
2018	J	`jnl`	Kickstarting Deep Reinforcement Learning. CoRR 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
2018	J	`jnl`	Malthusian Reinforcement Learning. CoRR Joel Z. Leibo, Julien Pérolat, Edward Hughes, Steven Wheelwright, Adam H. Marblestone, Edgar A. Duéñez-Guzmán, Peter Sunehag, Iain Dunning, Thore Graepel
2018	J	`jnl`	Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents. CoRR 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, Matthew M. Botvinick
2018	J	`jnl`	Unsupervised Predictive Memory in a Goal-Directed Agent. CoRR 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, Tim Harley, Josh Abramson, Shakir Mohamed, Danilo Jimenez Rezende, David Saxton, Adam Cain, Chloe Hillier, David Silver, Koray Kavukcuoglu, Matthew M. Botvinick, Demis Hassabis, Timothy P. Lillicrap
2018	A	`conf`	Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward. AAMAS 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
2017	—	`conf`	A multi-agent reinforcement learning model of common-pool resource appropriation. NIPS Julien Pérolat, Joel Z. Leibo, Vinícius Flores Zambaldi, Charles Beattie, Karl Tuyls, Thore Graepel
2017	J	`jnl`	A multi-agent reinforcement learning model of common-pool resource appropriation. CoRR Julien Pérolat, Joel Z. Leibo, Vinícius Flores Zambaldi, Charles Beattie, Karl Tuyls, Thore Graepel
2017	J	`jnl`	Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017. CoRR 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, Tom Schaul, Christopher Summerfield, Greg Wayne, Theophane Weber, Daan Wierstra, Shane Legg, Demis Hassabis
2017	J	`jnl`	Learning from Demonstrations for Real World Reinforcement Learning. CoRR 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
2017	B	`conf`	Learning to reinforcement learn. CogSci Jane Wang, Zeb Kurth-Nelson, Hubert Soyer, Joel Z. Leibo, Dhruva Tirumala, Rémi Munos, Charles Blundell, Dharshan Kumaran, Matt M. Botvinick
2017	A	`conf`	Multi-agent Reinforcement Learning in Sequential Social Dilemmas. AAMAS Joel Z. Leibo, Vinícius Flores Zambaldi, Marc Lanctot, Janusz Marecki, Thore Graepel
2017	J	`jnl`	Multi-agent Reinforcement Learning in Sequential Social Dilemmas. CoRR Joel Z. Leibo, Vinícius Flores Zambaldi, Marc Lanctot, Janusz Marecki, Thore Graepel
2017	—	`conf`	Reinforcement Learning with Unsupervised Auxiliary Tasks. ICLR Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, Tom Schaul, Joel Z. Leibo, David Silver, Koray Kavukcuoglu
2017	J	`jnl`	Symmetric Decomposition of Asymmetric Games. CoRR Karl Tuyls, Julien Pérolat, Marc Lanctot, Georg Ostrovski, Rahul Savani, Joel Z. Leibo, Toby Ord, Thore Graepel, Shane Legg
2017	J	`jnl`	Value-Decomposition Networks For Cooperative Multi-Agent Learning. CoRR 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
2016	J	`jnl`	DeepMind Lab. CoRR 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, Sarah York, Max Cant, Adam Cain, Adrian Bolton, Stephen Gaffney, Helen King, Demis Hassabis, Shane Legg, Stig Petersen
2016	A*	`conf`	How Important Is Weight Symmetry in Backpropagation? AAAI Qianli Liao, Joel Z. Leibo, Tomaso A. Poggio
2016	J	`jnl`	Learning to reinforcement learn. CoRR Jane X. Wang, Zeb Kurth-Nelson, Dhruva Tirumala, Hubert Soyer, Joel Z. Leibo, Rémi Munos, Charles Blundell, Dharshan Kumaran, Matthew M. Botvinick
2016	J	`jnl`	Model-Free Episodic Control. CoRR Charles Blundell, Benigno Uria, Alexander Pritzel, Yazhe Li, Avraham Ruderman, Joel Z. Leibo, Jack W. Rae, Daan Wierstra, Demis Hassabis
2016	J	`jnl`	Reinforcement Learning with Unsupervised Auxiliary Tasks. CoRR Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, Tom Schaul, Joel Z. Leibo, David Silver, Koray Kavukcuoglu
2016	J	`jnl`	Unsupervised learning of invariant representations. Theor. Comput. Sci. Fabio Anselmi, Joel Z. Leibo, Lorenzo Rosasco, Jim Mutch, Andrea Tacchetti, Tomaso A. Poggio
2016	—	`conf`	Using Fast Weights to Attend to the Recent Past. NIPS Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu
2016	J	`jnl`	Using Fast Weights to Attend to the Recent Past. CoRR Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu
2016	J	`jnl`	View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation. CoRR Joel Z. Leibo, Qianli Liao, Winrich Freiwald, Fabio Anselmi, Tomaso A. Poggio
2015	J	`jnl`	Approximate Hubel-Wiesel Modules and the Data Structures of Neural Computation. CoRR Joel Z. Leibo, Julien Cornebise, Sergio Gómez, Demis Hassabis
2015	J	`jnl`	How Important is Weight Symmetry in Backpropagation? CoRR Qianli Liao, Joel Z. Leibo, Tomaso A. Poggio
2015	J	`jnl`	The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex. PLoS Comput. Biol. Joel Z. Leibo, Qianli Liao, Fabio Anselmi, Tomaso A. Poggio
2014	—	`conf`	Subtasks of Unconstrained Face Recognition. VISAPP (2) Joel Z. Leibo, Qianli Liao, Tomaso A. Poggio
2014	J	`jnl`	Unsupervised learning of clutter-resistant visual representations from natural videos. CoRR Qianli Liao, Joel Z. Leibo, Tomaso A. Poggio
2013	J	`jnl`	Can a biologically-plausible hierarchy effectively replace face detection, alignment, and recognition pipelines? CoRR Qianli Liao, Joel Z. Leibo, Youssef Mroueh, Tomaso A. Poggio
2013	—	`conf`	Learning invariant representations and applications to face verification. NIPS Qianli Liao, Joel Z. Leibo, Tomaso A. Poggio
2013	—	`ch.`	Throwing Down the Visual Intelligence Gauntlet. Machine Learning for Computer Vision Cheston Tan, Joel Z. Leibo, Tomaso A. Poggio
2013	J	`jnl`	Unsupervised Learning of Invariant Representations in Hierarchical Architectures. CoRR Fabio Anselmi, Joel Z. Leibo, Lorenzo Rosasco, Jim Mutch, Andrea Tacchetti, Tomaso A. Poggio
2012	J	`jnl`	Learning and disrupting invariance in visual recognition with a temporal association rule. Frontiers Comput. Neurosci. Leyla Isik, Joel Z. Leibo, Tomaso A. Poggio
2011	—	`conf`	Why The Brain Separates Face Recognition From Object Recognition. NIPS Joel Z. Leibo, Jim Mutch, Tomaso A. Poggio