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Induction over Strategic Agents

Author

Listed:
  • Fidan Boylu

    (Department of Operations and Information Management, School of Business, University of Connecticut, Storrs, Connecticut 06269)

  • Haldun Aytug

    (Information Systems and Operations Management Department, The Warrington College of Business Administration, University of Florida, Gainesville, Florida 32611)

  • Gary J. Koehler

    (Information Systems and Operations Management Department, The Warrington College of Business Administration, University of Florida, Gainesville, Florida 32611)

Abstract

We study the problem where a decision maker needs to discover a classification rule to classify intelligent, self-interested agents. Agents may engage in strategic behavior to alter their characteristics for a favorable classification. We show how the decision maker can induce a classification rule that anticipates such behavior while still satisfying an important risk minimization principle.

Suggested Citation

  • Fidan Boylu & Haldun Aytug & Gary J. Koehler, 2010. "Induction over Strategic Agents," Information Systems Research, INFORMS, vol. 21(1), pages 170-189, March.
    • Handle: RePEc:inm:orisre:v:21:y:2010:i:1:p:170-189
    DOI: 10.1287/isre.1090.0272
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    References listed on IDEAS

    as
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    4. Eisenbeis, Robert A, 1987. "Credit Granting: A Comparative Analysis of Classification Procedures: Discussion," Journal of Finance, American Finance Association, vol. 42(3), pages 681-683, July.
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    Cited by:

    1. Asunur Cezar & Srinivasan Raghunathan & Sumit Sarkar, 2020. "Adversarial Classification: Impact of Agents’ Faking Cost on Firms and Agents," Production and Operations Management, Production and Operations Management Society, vol. 29(12), pages 2789-2807, December.
    2. Yuanfeng Cai & Zhengrui Jiang & Vijay Mookerjee, 2017. "How to Deal with Liars? Designing Intelligent Rule-Based Expert Systems to Increase Accuracy or Reduce Cost," INFORMS Journal on Computing, INFORMS, vol. 29(2), pages 268-286, May.
    3. Juheng Zhang & Xiaoping Liu & Xiao-Bai Li, 2020. "Predictive Analytics with Strategically Missing Data," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 1143-1156, October.
    4. Mehmet Eren Ahsen & Mehmet Ulvi Saygi Ayvaci & Srinivasan Raghunathan, 2019. "When Algorithmic Predictions Use Human-Generated Data: A Bias-Aware Classification Algorithm for Breast Cancer Diagnosis," Service Science, INFORMS, vol. 30(1), pages 97-116, March.
    5. Vijay Mookerjee & Radha Mookerjee & Alain Bensoussan & Wei T. Yue, 2011. "When Hackers Talk: Managing Information Security Under Variable Attack Rates and Knowledge Dissemination," Information Systems Research, INFORMS, vol. 22(3), pages 606-623, September.
    6. Zhang, Juheng & Aytug, Haldun, 2016. "Comparison of imputation methods for discriminant analysis with strategically hidden data," European Journal of Operational Research, Elsevier, vol. 255(2), pages 522-530.
    7. Juheng Zhang & Haldun Aytug & Gary J. Koehler, 2014. "Research Note —Discriminant Analysis with Strategically Manipulated Data," Information Systems Research, INFORMS, vol. 25(3), pages 654-662, September.

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