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The growing capabilities and increasingly widespread deployment of AI systems necessitate robust benchmarks for measuring their cooperative capabilities.
The Bargaining Problem
John F. Nash · 1950
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Diplomacy, 1959
A. Calhamer · 1959
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Reexamination of the perfectness concept for equilibrium points in extensive games
R. Selten · 1975
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An experimental analysis of ultimatum bargaining
Werner Güth, Rolf Schmittberger, and Bernd Schwarze · 1982
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Coalition-proof Nash Equilibria I. Concepts
B Douglas Bernheim, Bezalel Peleg, and Michael D Whinston · 1987
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Diplomat, an agent in a multi agent environment: An overview
S. Kraus and D. Lehmann · 1988
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Fairness in simple bargaining experiments
Robert Forsythe, Joel L Horowitz, Nathan E Savin, and Martin Sefton · 1994
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Thoughts on Programming a Diplomat
Michael Hall and Daniel Loeb · 1995
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A theory of fairness, competition, and cooperation
Ernst Fehr and Klaus M Schmidt · 1999
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A guide to webdiplomacy’s scoring systems and points, 1999
webDiplomacy · 1999
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Scaling Laws for Neural Language Models, January 2020
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B. Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei · 2001
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Social Utility in Ultimatum Bargaining
Michel J. J. Handgraaf, Eric Van Dijk, and David De Cremer · 2003
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Regret minimization in games with incomplete information
Martin Zinkevich, Michael Johanson, Michael Bowling, and Carmelo Piccione · 2007
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ImageNet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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The Turking Test: Can Language Models Understand Instructions?, October 2020
Avia Efrat and Omer Levy · 2010
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Open Problems in Cooperative AI, December 2020
Allan Dafoe, Edward Hughes, Yoram Bachrach, Tantum Collins, Kevin R. McKee, Joel Z. Leibo, Kate Larson, and Thore Graepel · 2012
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A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning · 2015
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DipBlue: A Diplomacy Agent with Strategic and Trust Reasoning:
André Ferreira, Henrique Lopes Cardoso, and Luis Paulo Reis · 2015
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Learning about the opponent in automated bilateral negotiation: a comprehensive survey of opponent modeling techniques
Tim Baarslag, Mark J. C. Hendrikx, Koen V. Hindriks, and Catholijn M. Jonker · 2016
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SQuAD: 100,000+ Questions for Machine Comprehension of Text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang · 2016
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D-Brane: a diplomacy playing agent for automated negotiations research
Dave De Jonge and Carles Sierra · 2017
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Deal or No Deal? End-to-End Learning for Negotiation Dialogues, June 2017
Mike Lewis, Denis Yarats, Yann N. Dauphin, Devi Parikh, and Dhruv Batra · 2017
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Decoupling Strategy and Generation in Negotiation Dialogues, August 2018
He He, Derek Chen, Anusha Balakrishnan, and Percy Liang · 2018
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Towards a Repeated Negotiating Agent that Treats People Individually: Cooperation, Social Value Orientation, & Machiavellianism
Johnathan Mell, Gale Lucas, Sharon Mozgai, Jill Boberg, Ron Artstein, and Jonathan Gratch · 2018
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Artificial Intelligence and Collusion
Francisco Beneke and Mark-Oliver Mackenrodt · 2019
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On the utility of learning about humans for human-ai coordination
Micah Carroll, Rohin Shah, Mark K Ho, Tom Griffiths, Sanjit Seshia, Pieter Abbeel, and Anca Dragan · 2019
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GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman · 2019
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The starcraft multi-agent challenge
S Whiteson, M Samvelyan, T Rashid, CS De Witt, G Farquhar, N Nardelli, TGJ Rudner, CM Hung, PHS Torr, and J Foerster · 2019
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Learning to Play No-Press Diplomacy with Best Response Policy Iteration
Thomas Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian Gemp, Thomas Hudson, Nicolas Porcel, Marc Lanctot, Julien Perolat, Richard Everett, Satinder Singh, Thore Graepel, and Yoram Bachrach · 2020
Cited alongside, same era.
The hanabi challenge: A new frontier for ai research
Nolan Bard, Jakob N Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, H Francis Song, Emilio Parisotto, Vincent Dumoulin, Subhodeep Moitra, Edward Hughes, et al · 2020
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Training language models to follow instructions with human feedback, March 2022
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe · 2022
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Discovering Language Model Behaviors with Model-Written Evaluations, 2022
Ethan Perez, Sam Ringer, Kamilė Lukošiūtė, Karina Nguyen, Edwin Chen, Scott Heiner, Craig Pettit, Catherine Olsson, Sandipan Kundu, Saurav Kadavath, Andy Jones, Anna Chen, Ben Mann, Brian Israel, Bryan Seethor, Cameron McKinnon, Christopher Olah, Da Yan, Daniela Amodei, Dario Amodei, Dawn Drain, Dustin Li, Eli Tran-Johnson, Guro Khundadze, Jackson Kernion, James Landis, Jamie Kerr, Jared Mueller, Jeeyoon Hyun, Joshua Landau, Kamal Ndousse, Landon Goldberg, Liane Lovitt, Martin Lucas, Michael Sellitto, Miranda Zhang, Neerav Kingsland, Nelson Elhage, Nicholas Joseph, Noemí Mercado, Nova DasSarma, Oliver Rausch, Robin Larson, Sam McCandlish, Scott Johnston, Shauna Kravec, Sheer El Showk, Tamera Lanham, Timothy Telleen-Lawton, Tom Brown, Tom Henighan, Tristan Hume, Yuntao Bai, Zac Hatfield-Dodds, Jack Clark, Samuel R. Bowman, Amanda Askell, Roger Grosse, Danny Hernandez, Deep Ganguli, Evan Hubinger, Nicholas Schiefer, and Jared Kaplan · 2022
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Differential technology development: A responsible innovation principle for navigating technology risks
Jonas Sandbrink, Hamish Hobbs, Jacob Swett, Allan Dafoe, and Anders Sandberg · 2022
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Artificial Intelligence & Cooperation
Elisa Bertino, Finale Doshi-Velez, Maria Gini, Daniel Lopresti, and David Parkes · 2020
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Artificial Intelligence, Algorithmic Pricing, and Collusion
Emilio Calvano, Giacomo Calzolari, Vincenzo Denicolò, and Sergio Pastorello · 2020
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Learning to resolve alliance dilemmas in many-player zero-sum games
Edward Hughes, Thomas W Anthony, Tom Eccles, Joel Z Leibo, David Balduzzi, and Yoram Bachrach · 2020
Cited alongside, same era.
Too many cooks: Coordinating multi-agent collaboration through inverse planning
Rose E Wang, Sarah A Wu, James A Evans, Joshua B Tenenbaum, David C Parkes, and Max Kleiman-Weiner · 2020
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No-press diplomacy from scratch
Anton Bakhtin, David Wu, Adam Lerer, and Noam Brown · 2021
Cited alongside, same era.
CaSiNo: A Corpus of Campsite Negotiation Dialogues for Automatic Negotiation Systems, April 2021
Kushal Chawla, Jaysa Ramirez, Rene Clever, Gale Lucas, Jonathan May, and Jonathan Gratch · 2021
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Evaluating Large Language Models Trained on Code, July 2021
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Josh Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, and Wojciech Zaremba · 2021
Cited alongside, same era.
Later among the works it cites.
Beyond neural scaling laws: beating power law scaling via data pruning, June 2022
Ben Sorscher, Robert Geirhos, Shashank Shekhar, Surya Ganguli, and Ari S. Morcos · 2022
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CHAI: A CHatbot AI for Task-Oriented Dialogue with Offline Reinforcement Learning, April 2022
Siddharth Verma, Justin Fu, Mengjiao Yang, and Sergey Levine · 2022
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The ai economist: Taxation policy design via two-level deep multiagent reinforcement learning
Stephan Zheng, Alexander Trott, Sunil Srinivasa, David C Parkes, and Richard Socher · 2022
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Llm-deliberation: Evaluating llms with interactive multi-agent negotiation games
Sahar Abdelnabi, Amr Gomaa, Sarath Sivaprasad, Lea Schönherr, and Mario Fritz · 2023
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Playing repeated games with Large Language Models, May 2023
Elif Akata, Lion Schulz, Julian Coda-Forno, Seong Joon Oh, Matthias Bethge, and Eric Schulz · 2023
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Frontier AI Regulation: Managing Emerging Risks to Public Safety, September 2023
Markus Anderljung, Joslyn Barnhart, Anton Korinek, Jade Leung, Cullen O’Keefe, Jess Whittlestone, Shahar Avin, Miles Brundage, Justin Bullock, Duncan Cass-Beggs, Ben Chang, Tantum Collins, Tim Fist, Gillian Hadfield, Alan Hayes, Lewis Ho, Sara Hooker, Eric Horvitz, Noam Kolt, Jonas Schuett, Yonadav Shavit, Divya Siddarth, Robert Trager, and Kevin Wolf · 2023
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Model Card and Evaluations for Claude Models, 2023
Anthropic · 2023
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Taken out of context: On measuring situational awareness in LLMs, September 2023
Lukas Berglund, Asa Cooper Stickland, Mikita Balesni, Max Kaufmann, Meg Tong, Tomasz Korbak, Daniel Kokotajlo, and Owain Evans · 2023
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Towards the Scalable Evaluation of Cooperativeness in Language Models, March 2023
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Foundations of Cooperative AI
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Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback
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Strategic Reasoning with Language Models, May 2023
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Palantir Technologies Inc · 2023
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GPT-4 Technical Report
OpenAI · 2023
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Cooperating with machines
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