Decision making with limited feedback: Error bounds for predictive policing and recidivism prediction

Decision making with limited feedback: Error bounds for predictive policing and recidivism prediction. Ensign, D., Frielder, S. A, Neville, S., Scheidegger, C., & Venkatasubramanian, S.
abstract bibtex

In this paper, we focus on the problems of recidivism prediction and predictive policing. We present the ﬁrst algorithms with provable regret for these problems, by showing that both problems (and others like these) can be abstracted into a general reinforcement learning framework called partial monitoring. We also discuss the policy implications of these solutions.

@article{ensign_decision_nodate,
	title = {Decision making with limited feedback: Error bounds for predictive policing and recidivism prediction},
	abstract = {In this paper, we focus on the problems of recidivism prediction and predictive policing. We present the ﬁrst algorithms with provable regret for these problems, by showing that both problems (and others like these) can be abstracted into a general reinforcement learning framework called partial monitoring. We also discuss the policy implications of these solutions.},
	pages = {9},
	author = {Ensign, Danielle and Frielder, Sorelle A and Neville, Scott and Scheidegger, Carlos and Venkatasubramanian, Suresh},
	langid = {english}
}

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