mlsanityData to 7 Oct 2026

How Do Classifiers Induce Agents To Invest Effort Strategically?

arXiv 1807.05307 ↗First posted 13 Jul 2018cs.LG cs.CY cs.DScited by 82

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Abstract (arXiv)

Algorithms are often used to produce decision-making rules that classify or evaluate individuals. When these individuals have incentives to be classified a certain way, they may behave strategically to influence their outcomes. We develop a model for how strategic agents can invest effort in order to change the outcomes they receive, and we give a tight characterization of when such agents can be incentivized to invest specified forms of effort into improving their outcomes as opposed to "gaming" the classifier. We show that whenever any "reasonable" mechanism can do so, a simple linear mechanism suffices.

Key facts. Cited by 82 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Jul 2018.

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Citing papers per year: 2021: 12; 2022: 11; 2023: 20; 2024: 13; 2025: 13; 2026: 13.

82 papers.

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  1. 2021How to Learn when Data Reacts to Your Model: Performative Gradient Descentcited by 70
  2. 2021Strategic Classification in the Darkcited by 66
  3. 2021Strategic Classification Made Practicalcited by 58
  4. 2021Who Leads and Who Follows in Strategic Classification?cited by 53
  5. 2021Information Discrepancy in Strategic Learningcited by 48
  6. 2021Alternative Microfoundations for Strategic Classificationcited by 47
  7. 2022Performative Powercited by 42
  8. 2022Modeling Content Creator Incentives on Algorithm-Curated Platformscited by 35
  9. 2022Supply-Side Equilibria in Recommender Systemscited by 33
  10. 2021Stateful Strategic Regressioncited by 32
  11. 2021Strategic Instrumental Variable Regression: Recovering Causal Relationships From Strategic Responsescited by 32
  12. 2023Causal Strategic Classification: A Tale of Two Shiftscited by 30
38 more
  1. 2022On classification of strategic agents who can both game and improvecited by 27
  2. 2023Strategic Classification under Unknown Personalized Manipulationcited by 23
  3. 2024Contracting with a Learning Agentcited by 22
  4. 2021Strategic Rankingcited by 21
  5. 2023Plug-in Performative Optimizationcited by 20
  6. 2022What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspectivecited by 18
  7. 2023Fundamental Bounds on Online Strategic Classificationcited by 17
  8. 2021Bayesian Persuasion for Algorithmic Recoursecited by 14
  9. 2023Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shiftscited by 14
  10. 2024Clickbait vs. Quality: How Engagement-Based Optimization Shapes the Content Landscape in Online Platformscited by 13
  11. 2023A Classification of Feedback Loops and Their Relation to Biases in Automated Decision-Making Systemscited by 12
  12. 2023Auditing for Human Expertisecited by 12
  13. 2024Non-linear Welfare-Aware Strategic Learningcited by 12
  14. 2023Performative Prediction with Bandit Feedback: Learning through Reparameterizationcited by 11
  15. 2024Accounting for AI and Users Shaping One Another: The Role of Mathematical Modelscited by 11
  16. 2024Addressing Polarization and Unfairness in Performative Predictioncited by 11
  17. 2023Strategic Apple Tastingcited by 10
  18. 2023Delegated Classificationcited by 10
  19. 2023Deep Contract Design via Discontinuous Networkscited by 10
  20. 2021Model Transferability With Responsive Decision Subjectscited by 9
  21. 2023GAM Coach: Towards Interactive and User-centered Algorithmic Recoursecited by 9
  22. 2023On the Actionability of Outcome Predictioncited by 9
  23. 2024Automating Data Annotation under Strategic Human Agents: Risks and Potential Solutionscited by 9
  24. 2022Addressing Strategic Manipulation Disparities in Fair Classificationcited by 8
  25. 2023Sequential Strategic Screeningcited by 8
  26. 2024Learning under Imitative Strategic Behavior with Unforeseeable Outcomescited by 8
  27. 2024Strategic Littlestone Dimension: Improved Bounds on Online Strategic Classificationcited by 8
  28. 2025Incentivizing Desirable Effort Profiles in Strategic Classification: The Role of Causality and Uncertaintycited by 8
  29. 2025Performative Validity of Recourse Explanationscited by 8
  30. 2022Setting Fair Incentives to Maximize Improvementcited by 7
  31. 2023Choosing the Right Weights: Balancing Value, Strategy, and Noise in Recommender Systemscited by 7
  32. 2024Algorithmic Decision-Making under Agents with Persistent Improvementcited by 7
  33. 2024Strategic Classification With Externalitiescited by 7
  34. 2025PAC Learning with Improvementscited by 6
  35. 2022Strategyproof Decision-Making in Panel Data Settings and Beyondcited by 4
  36. 2023Prediction without Preclusion: Recourse Verification with Reachable Setscited by 4
  37. 2025How Strategic Agents Respond: Comparing Analytical Models with LLM-Generated Responses in Strategic Classificationcited by 4
  38. 2022Margin-distancing for safe model explanationcited by 3

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