An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
The cost-minimizing inverse classification problem: a genetic algorithm approach
Decision Support Systems
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Debiasing Training Data for Inductive Expert System Construction
IEEE Transactions on Knowledge and Data Engineering
Machine Learning
Implicit Negotiation in Repeated Games
ATAL '01 Revised Papers from the 8th International Workshop on Intelligent Agents VIII
Classes of kernels for machine learning: a statistics perspective
The Journal of Machine Learning Research
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Active Feature-Value Acquisition for Classifier Induction
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Lying on the Web: Implications for Expert Systems Redesign
Information Systems Research
Toward economic machine learning and utility-based data mining
UBDM '05 Proceedings of the 1st international workshop on Utility-based data mining
Learning in the Presence of Self-Interested Agents
HICSS '06 Proceedings of the 39th Annual Hawaii International Conference on System Sciences - Volume 07
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
An overview of statistical learning theory
IEEE Transactions on Neural Networks
Decision Support Systems
Decision Support Systems
Information Technology and Management
Information Systems Research
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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.