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Many human-facing algorithms -- including those that power recommender systems or hiring decision tools -- are trained on data provided by their users.
“Continuous Time Repeated Games”
James Bergin and W MacLeod · 1993
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“Self-Confirming Equilibrium”
Drew Fudenberg and David Levine · 1993
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“Subjective Equilibrium in Repeated Games”
Ehud Kalai and Ehud Lehrer · 1993
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“Multi-agent reinforcement learning: Independent vs. cooperative agents”
Ming Tan · 1993
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“Continuous Time Repeated Games”
James Bergin and W MacLeod · 1993
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“Self-Confirming Equilibrium”
Drew Fudenberg and David Levine · 1993
Earlier work this paper cites.
“Subjective Equilibrium in Repeated Games”
Ehud Kalai and Ehud Lehrer · 1993
Earlier work this paper cites.
“Multi-agent reinforcement learning: Independent vs. cooperative agents”
Ming Tan · 1993
Earlier work this paper cites.
“Subjective games and equilibria”
Ehud Kalai and Ehud Lehrer · 1995
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“Subjective games and equilibria”
Ehud Kalai and Ehud Lehrer · 1995
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“Trust and distrust in organizations: Emerging perspectives, enduring questions”
Roderick Kramer · 1999
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“Trust and distrust in organizations: Emerging perspectives, enduring questions”
Roderick Kramer · 1999
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“Securing trust online: Wisdom or oxymoron”
Helen Nissenbaum · 2001
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“Securing trust online: Wisdom or oxymoron”
Helen Nissenbaum · 2001
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“Repeated games and reputations: Long-Run relationships”
George Mailath and Larry Samuelson · 2006
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“Repeated games and reputations: Long-Run relationships”
George Mailath and Larry Samuelson · 2006
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“Mechanism Design via Differential Privacy”
Frank McSherry and Kunal Talwar · 2007
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“Mechanism Design via Differential Privacy”
Frank McSherry and Kunal Talwar · 2007
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“A comprehensive survey of multiagent reinforcement learning”
Lucian Busoniu, Robert Babuska and Bart De · 2008
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“A comprehensive survey of multiagent reinforcement learning”
Lucian Busoniu, Robert Babuska and Bart De · 2008
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“On the Equilibria of Alternating Move Games”
Aaron Roth, Maria Balcan, Adam Kalai and Yishay Mansour · 2010
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“On the Equilibria of Alternating Move Games”
Aaron Roth, Maria Balcan, Adam Kalai and Yishay Mansour · 2010
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“Static prediction games for adversarial learning problems” Accessed: 2023-10-31
Michael Brückner, Christian Kanzow and Tobias Scheffer · 2012
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“Approximately optimal mechanism design via differential privacy”
Kobbi Nissim, Rann Smorodinsky and Moshe Tennenholtz · 2012
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“Static prediction games for adversarial learning problems” Accessed: 2023-10-31
Michael Brückner, Christian Kanzow and Tobias Scheffer · 2012
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“Approximately optimal mechanism design via differential privacy”
Kobbi Nissim, Rann Smorodinsky and Moshe Tennenholtz · 2012
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“Learning prices for repeated auctions with strategic buyers”
Kareem Amin, Afshin Rostamizadeh and Umar Syed · 2013
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“Learning prices for repeated auctions with strategic buyers”
Kareem Amin, Afshin Rostamizadeh and Umar Syed · 2013
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“Informational herding with model misspecification”
J Bohren · 2016
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“Berk–Nash equilibrium: A framework for modeling agents with misspecified models”
Ignacio Esponda and Demian Pouzo · 2016
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“Cooperative inverse reinforcement learning”
Dylan Hadfield-Menell, Anca Dragan, Pieter Abbeel and Stuart Russell · 2016
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“Strategic Classification”
Moritz Hardt, Nimrod Megiddo, Christos Papadimitriou and Mary Wootters · 2016
Earlier work this paper cites.
“Informational herding with model misspecification”
J Bohren · 2016
Earlier work this paper cites.
“Berk–Nash equilibrium: A framework for modeling agents with misspecified models”
Ignacio Esponda and Demian Pouzo · 2016
Earlier work this paper cites.
“Cooperative inverse reinforcement learning”
Dylan Hadfield-Menell, Anca Dragan, Pieter Abbeel and Stuart Russell · 2016
Earlier work this paper cites.
“Strategic Classification”
Moritz Hardt, Nimrod Megiddo, Christos Papadimitriou and Mary Wootters · 2016
Earlier work this paper cites.
“Active learning with a misspecified prior”
D Fudenberg, G Romanyuk and P Strack · 2017
Cited alongside, same era.
“Active learning with a misspecified prior”
D Fudenberg, G Romanyuk and P Strack · 2017
Cited alongside, same era.
“Strategic Classification from Revealed Preferences”
Jinshuo Dong, Aaron Roth, Zachary Schutzman, Bo Waggoner and Zhiwei Wu · 2018
Cited alongside, same era.
“Strategic Classification from Revealed Preferences”
Jinshuo Dong, Aaron Roth, Zachary Schutzman, Bo Waggoner and Zhiwei Wu · 2018
Cited alongside, same era.
“Learning auctions with robust incentive guarantees”
Jacob Abernethy, Rachel Cummings, Bhuvesh Kumar, Sam Taggart and Jamie Morgenstern · 2019
Cited alongside, same era.
“Beyond accuracy: The role of mental models in human-AI team performance”
Gagan Bansal, Besmira Nushi, Ece Kamar, Walter Lasecki, Daniel Weld and Eric Horvitz · 2019
Cited alongside, same era.
“Who Leads and Who Follows in Strategic Classification?”
Tijana Zrnic, Eric Mazumdar, Shankar Sastry and Michael Jordan · 2021
Later among the works it cites.
“Investigating the relationship between AI and trust in human-AI collaboration”
Ying Bao, Xusen Cheng, Triparna De and Gert-Jan De · 2021
Later among the works it cites.
“Learning with heterogeneous misspecified models: Characterization and robustness”
J Bohren and Daniel Hauser · 2021
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“Revenue-Incentive Tradeoffs in Dynamic Reserve Pricing”
Yuan Deng, Sebastien Lahaie, Vahab Mirrokni and Song Zuo · 2021
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“Limit points of endogenous misspecified learning”
Drew Fudenberg, Giacomo Lanzani and Philipp Strack · 2021
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“Strategic Classification in the Dark”
Ganesh Ghalme, Vineet Nair, Itay Eilat, Inbal Talgam-Cohen and Nir Rosenfeld · 2021
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“Trust Engineering for Human-AI Teams”
Neta Ezer, Sylvain Bruni, Yang Cai, Sam Hepenstal, Christopher Miller and Dylan Schmorrow · 2019
Cited alongside, same era.
“Incentive-Compatible Learning of Reserve Prices for Repeated Auctions”
Yash Kanoria and Hamid Nazerzadeh · 2019
Cited alongside, same era.
“Human-AI Collaboration in Data Science: Exploring Data Scientists’ Perceptions of Automated AI”
Dakuo Wang, Justin Weisz, Michael Muller, Parikshit Ram, Werner Geyer, Casey Dugan, Yla Tausczik, Horst Samulowitz and Alexander Gray · 2019
Cited alongside, same era.
“Multi-Agent Adversarial Inverse Reinforcement Learning”
Lantao Yu, Jiaming Song and Stefano Ermon · 2019
Cited alongside, same era.
“Learning auctions with robust incentive guarantees”
Jacob Abernethy, Rachel Cummings, Bhuvesh Kumar, Sam Taggart and Jamie Morgenstern · 2019
Cited alongside, same era.
“Beyond accuracy: The role of mental models in human-AI team performance”
Gagan Bansal, Besmira Nushi, Ece Kamar, Walter Lasecki, Daniel Weld and Eric Horvitz · 2019
Cited alongside, same era.
Later among the works it cites.
“Multi-agent Bayesian Learning with Best Response Dynamics: Convergence and Stability”
M Wu, S Amin and A Ozdaglar · 2021
Later among the works it cites.
“Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms”
Kaiqing Zhang, Zhuoran Yang and Tamer Başar · 2021
Later among the works it cites.
““An Ideal Human”: Expectations of AI Teammates in Human-AI Teaming”
Rui Zhang, Nathan McNeese, Guo Freeman and Geoff Musick · 2021
Later among the works it cites.
“Who Leads and Who Follows in Strategic Classification?”
Tijana Zrnic, Eric Mazumdar, Shankar Sastry and Michael Jordan · 2021
Later among the works it cites.
“Performative Prediction in a Stateful World”
Gavin Brown, Shlomi Hod and Iden Kalemaj · 2022
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“A Game-Theoretic Perspective on Trust in Recommendation”
S Cen, A Ilyas and A Madry · 2022
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“Learning in Stackelberg Games with Non-myopic Agents”
Nika Haghtalab, Thodoris Lykouris, Sloan Nietert and Alexander Wei · 2022
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“The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization”
Jon Kleinberg, Sendhil Mullainathan and Manish Raghavan · 2022
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“Generalized Strategic Classification and the Case of Aligned Incentives”
Sagi Levanon and Nir Rosenfeld · 2022
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“Reading Between the Lines: Modeling User Behavior and Costs in AI-Assisted Programming”, 2022
Hussein Mozannar, Gagan Bansal, Adam Fourney and Eric Horvitz · 2022
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“Learning in Repeated Auctions”
Thomas Nedelec, Clément Calauzènes, Noureddine El and Vianney Perchet · 2022
Later among the works it cites.
“Learning to like TikTok . . . and not: Algorithm awareness as process”
Ignacio Siles, Luciana Valerio-Alfaro and Ariana Meléndez-Moran · 2022
Later among the works it cites.
“How to Tame “Your” Algorithm: LGBTQ+ Users’ Domestication of TikTok”
Ellen Simpson, Andrew Hamann and Bryan Semaan · 2022
Later among the works it cites.
“Performative Prediction in a Stateful World”
Gavin Brown, Shlomi Hod and Iden Kalemaj · 2022
Later among the works it cites.
“A Game-Theoretic Perspective on Trust in Recommendation”
S Cen, A Ilyas and A Madry · 2022
Later among the works it cites.
“Learning in Stackelberg Games with Non-myopic Agents”
Nika Haghtalab, Thodoris Lykouris, Sloan Nietert and Alexander Wei · 2022
Later among the works it cites.
“The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization”
Jon Kleinberg, Sendhil Mullainathan and Manish Raghavan · 2022
Later among the works it cites.
“Generalized Strategic Classification and the Case of Aligned Incentives”
Sagi Levanon and Nir Rosenfeld · 2022
Later among the works it cites.
“Reading Between the Lines: Modeling User Behavior and Costs in AI-Assisted Programming”, 2022
Hussein Mozannar, Gagan Bansal, Adam Fourney and Eric Horvitz · 2022
Later among the works it cites.
“Learning in Repeated Auctions”
Thomas Nedelec, Clément Calauzènes, Noureddine El and Vianney Perchet · 2022
Later among the works it cites.
“Learning to like TikTok . . . and not: Algorithm awareness as process”
Ignacio Siles, Luciana Valerio-Alfaro and Ariana Meléndez-Moran · 2022
Later among the works it cites.
“How to Tame “Your” Algorithm: LGBTQ+ Users’ Domestication of TikTok”
Ellen Simpson, Andrew Hamann and Bryan Semaan · 2022
Later among the works it cites.
“Measuring Strategization in Recommendation: Users Adapt Their Behavior to Shape Future Content”
Sarah. Cen, Andrew Ilyas, Jennifer Allen, Hannah Li, David Rand and Aleksander Madry · 2023
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“Recommending to Strategic Users”
Andreas Haupt, Dylan Hadfield-Menell and Chara Podimata · 2023
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“Exploring Trust in Human–AI Collaboration in the Context of Multiplayer Online Games”
Keke Hou, Tingting Hou and Lili Cai · 2023
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“Investigating How Users Design Everyday Intelligent Systems in Use”
Hankyung Kim and Youn-Kyung Lim · 2023
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“Measuring Strategization in Recommendation: Users Adapt Their Behavior to Shape Future Content”
Sarah. Cen, Andrew Ilyas, Jennifer Allen, Hannah Li, David Rand and Aleksander Madry · 2023
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“Recommending to Strategic Users”
Andreas Haupt, Dylan Hadfield-Menell and Chara Podimata · 2023
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“Exploring Trust in Human–AI Collaboration in the Context of Multiplayer Online Games”
Keke Hou, Tingting Hou and Lili Cai · 2023
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“Investigating How Users Design Everyday Intelligent Systems in Use”
Hankyung Kim and Youn-Kyung Lim · 2023
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