Parole Board Decision-Making using Adversarial Risk Analysis

Chaitanya Joshi, Charné Nel, Javier Cano and Devon L.L. Polaschek

The American Statistician, 2024, vol. 78, issue 3, 345-358

Abstract: Adversarial Risk Analysis (ARA) allows for much more realistic modeling of game theoretical decision problems than Bayesian game theory. While ARA solutions for various applications have been discussed in the literature, we have not encountered a manuscript that assesses ARA in a real-life case study involving actual decision-makers. In this study, we present an ARA solution for the Parole Board decision problem. To elicit the Parole Board’s probabilities and utilities regarding the convict’s choices and resulting consequences, as well as their own subjective beliefs about such probabilities and utilities, we conducted a detailed interview with two current members of the New Zealand Parole Board, using a realistic case report. Subsequently, we derived the optimal ARA decision for different scenarios. This study highlights the advantages and challenges of the ARA methodology for real-life decision-making in the presence of an adversary.

Date: 2024
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DOI: 10.1080/00031305.2024.2303416

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