{"total":46,"rows":[{"id":"2307.00168","title":"U-Calibration: Forecasting for an Unknown Agent","created":"2023-06-30","cited_by_count":46,"area":null},{"id":"2205.08562","title":"Strategizing against Learners in Bayesian Games","created":"2022-05-17","cited_by_count":34,"area":null},{"id":"2310.19647","title":"Fast swap regret minimization and applications to approximate correlated equilibria","created":"2023-10-30","cited_by_count":32,"area":null},{"id":"2306.02704","title":"Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents","created":"2023-06-05","cited_by_count":25,"area":null},{"id":"2401.16198","title":"Contracting with a Learning Agent","created":"2024-01-29","cited_by_count":23,"area":null},{"id":"2110.11855","title":"Auctions Between Regret-Minimizing Agents","created":"2021-10-22","cited_by_count":22,"area":null},{"id":"2305.19496","title":"Is Learning in Games Good for the Learners?","created":"2023-05-31","cited_by_count":20,"area":null},{"id":"2112.07640","title":"How and Why to Manipulate Your Own Agent: On the Incentives of Users of Learning Agents","created":"2021-12-14","cited_by_count":17,"area":null},{"id":"2502.09332","title":"Full Swap Regret and Discretized Calibration","created":"2025-02-13","cited_by_count":15,"area":null},{"id":"2210.07773","title":"Diversified Recommendations for Agents with Adaptive Preferences","created":"2022-09-20","cited_by_count":9,"area":null},{"id":"2402.08637","title":"Strategizing against No-Regret Learners in First-Price Auctions","created":"2024-02-13","cited_by_count":8,"area":null},{"id":"2407.04889","title":"Maximizing utility in multi-agent environments by anticipating the behavior of other learners","created":"2024-07-05","cited_by_count":8,"area":null},{"id":"2502.20229","title":"Swap Regret and Correlated Equilibria Beyond Normal-Form Games","created":"2025-02-27","cited_by_count":8,"area":null},{"id":"2302.03719","title":"Persuading a Behavioral Agent: Approximately Best Responding and Learning","created":"2023-02-07","cited_by_count":7,"area":null},{"id":"2402.07363","title":"Strategically-Robust Learning Algorithms for Bidding in First-Price Auctions","created":"2024-02-12","cited_by_count":7,"area":null},{"id":"2409.03956","title":"Algorithmic Collusion Without Threats","created":"2024-09-06","cited_by_count":7,"area":null},{"id":"2301.12595","title":"Adversarial Attacks on Adversarial Bandits","created":"2023-01-30","cited_by_count":6,"area":null},{"id":"2402.09721","title":"Generalized Principal-Agent Problem with a Learning Agent","created":"2024-02-15","cited_by_count":6,"area":null},{"id":"2502.00204","title":"Nearly-Optimal Bandit Learning in Stackelberg Games with Side Information","created":"2025-01-31","cited_by_count":6,"area":null},{"id":"2403.00188","title":"Impact of Decentralized Learning on Player Utilities in Stackelberg Games","created":"2024-02-29","cited_by_count":5,"area":null},{"id":"2408.08272","title":"Is Knowledge Power? On the (Im)possibility of Learning from Strategic Interactions","created":"2024-08-15","cited_by_count":5,"area":null},{"id":"2506.01936","title":"Should Decision-Makers Reveal Classifiers in Online Strategic Classification?","created":"2025-06-02","cited_by_count":5,"area":null},{"id":"2406.07585","title":"Rate-Preserving Reductions for Blackwell Approachability","created":"2024-06-10","cited_by_count":4,"area":null},{"id":"2502.18582","title":"Learning and Computation of $\\Phi$-Equilibria at the Frontier of Tractability","created":"2025-02-25","cited_by_count":4,"area":null},{"id":"2405.20880","title":"Games with Payments between Learning Agents","created":"2024-05-31","cited_by_count":3,"area":null},{"id":"2412.18297","title":"Learning to Play Against Unknown Opponents","created":"2024-12-24","cited_by_count":3,"area":null},{"id":"2511.01852","title":"Proximal Regret and Proximal Correlated Equilibria: A New Tractable Solution Concept for Online Learning and Games","created":"2025-11-03","cited_by_count":3,"area":null},{"id":"2407.10207","title":"Learning to Steer Markovian Agents under Model Uncertainty","created":"2024-07-14","cited_by_count":2,"area":null},{"id":"2502.11673","title":"Best of Both Worlds: Regret Minimization versus Minimax Play","created":"2025-02-17","cited_by_count":2,"area":null},{"id":"2503.04202","title":"Computational Intractability of Strategizing against Online Learners","created":"2025-03-06","cited_by_count":2,"area":null},{"id":"2509.11357","title":"Online Omniprediction with Long-Term Constraints","created":"2025-09-14","cited_by_count":2,"area":null},{"id":"2601.03853","title":"From No-Regret to Strategically Robust Learning in Repeated Auctions","created":"2026-01-07","cited_by_count":2,"area":null},{"id":"2602.06264","title":"Swap Regret Minimization Through Response-Based Approachability","created":"2026-02-05","cited_by_count":2,"area":null},{"id":"2602.08862","title":"Near-optimal Swap Regret Minimization for Convex Losses","created":"2026-02-09","cited_by_count":2,"area":null},{"id":"2202.09364","title":"Playing against no-regret players","created":"2022-02-16","cited_by_count":1,"area":null},{"id":"2406.18805","title":"Online Stackelberg Optimization via Nonlinear Control","created":"2024-06-27","cited_by_count":1,"area":null},{"id":"2411.06069","title":"Model Selection for Average Reward RL with Application to Utility Maximization in Repeated Games","created":"2024-11-09","cited_by_count":1,"area":null},{"id":"2510.22471","title":"Learning Local Stackelberg Equilibria from Repeated Interactions with a Learning Agent","created":"2025-10-26","cited_by_count":1,"area":null},{"id":"2207.04054","title":"Online Learning in Supply-Chain Games","created":"2022-07-08","cited_by_count":0,"area":null},{"id":"2301.11802","title":"Decentralized Online Bandit Optimization on Directed Graphs with Regret Bounds","created":"2023-01-27","cited_by_count":0,"area":null},{"id":"2302.06652","title":"Achieving Better Regret against Strategic Adversaries","created":"2023-02-13","cited_by_count":0,"area":null},{"id":"2407.00419","title":"On the Complexity of Learning to Cooperate with Populations of Socially Rational Agents","created":"2024-06-29","cited_by_count":0,"area":null},{"id":"2603.22348","title":"Learning Safely Without Knowing the World:COMPASS-Hedge","created":"2026-03-22","cited_by_count":0,"area":null},{"id":"2604.05129","title":"No Coin Left Behind: Maximizing Strategic Surplus Against No-Regret Dynamics","created":"2026-04-06","cited_by_count":0,"area":null},{"id":"2606.02363","title":"Minimax-Optimal Policy Regret in Partially Observable Markov Games","created":"2026-06-01","cited_by_count":0,"area":null},{"id":"2606.04931","title":"Mean-based algorithms: A lower bound and regret","created":"2026-06-03","cited_by_count":0,"area":null}],"next_cursor":null}