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Induction over constrained strategic agents

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  • Boylu, Fidan
  • Aytug, Haldun
  • Koehler, Gary J.

Abstract

In a new learning paradigm called Induction over Strategic Agents, the principal anticipates possible alteration of attributes by agents wishing to achieve a positive classification. In many cases, agents are constrained on how an attribute can be modified. For example, attribute values may have upper and lower bounds or they may need to belong to a certain set of possible values such as binary valued attributes like "pays bills on time" or be linearly dependent like the relationships between accounting entries in an income statement. In this paper, we explore Induction over Strategic Agents for a class of problems where attributes are binary values.

Suggested Citation

  • Boylu, Fidan & Aytug, Haldun & Koehler, Gary J., 2010. "Induction over constrained strategic agents," European Journal of Operational Research, Elsevier, vol. 203(3), pages 698-705, June.
    • Handle: RePEc:eee:ejores:v:203:y:2010:i:3:p:698-705
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    References listed on IDEAS

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    1. Kar Yan Tam & Melody Y. Kiang, 1992. "Managerial Applications of Neural Networks: The Case of Bank Failure Predictions," Management Science, INFORMS, vol. 38(7), pages 926-947, July.
    2. Bart Baesens & Rudy Setiono & Christophe Mues & Jan Vanthienen, 2003. "Using Neural Network Rule Extraction and Decision Tables for Credit-Risk Evaluation," Management Science, INFORMS, vol. 49(3), pages 312-329, March.
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    Cited by:

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    2. 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.
    3. 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.
    4. 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.
    5. 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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