An Adversarial Risk Analysis Framework for Batch Acceptance Problems

DOI10.1287/deca.2020.0420OpenAlexW3120801636MaRDI QIDQ4991777

Refik Soyer, Jorge González-Ortega, Fabrizio Ruggeri, David Ríos Insua

Publication date: 3 June 2021

Published in: Decision Analysis (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10261/262047

zbMATH Keywords

securitydata manipulationadversarial hypothesis testingreview spam

Mathematics Subject Classification ID

Game theory, economics, finance, and other social and behavioral sciences (91-XX)

Cites Work

• Unnamed Item
• Classifier evaluation and attribute selection against active adversaries
• Defending against multiple different attackers
• Modeling secrecy and deception in a multiple-period attacker-defender signaling game
• Level-\(k\) reasoning in a generalized beauty contest
• On selecting a prior for the precision parameter of Dirichlet process mixture models
• A Bayesian analysis of some nonparametric problems
• Acceptance Sampling in Quality Control
• Optimal control of admission to a quenching system
• On the Evidence Needed to Reach Agreed Action Between Adversaries, with Application to Acceptance Sampling
• Governments' and Terrorists' Defense and Attack in a T-Period Game
• Deterring the Smuggling of Nuclear Weapons in Container Freight Through Detection and Retaliation
• Robust Adversarial Risk Analysis: A Level-k Approach
• Acceptance sampling in a producer—supplier conflicting environment: Risk neutral case
• A large‐scale linear programming model for finding optimal container inspection strategies
• Adversarial Risk Analysis
• Uncertain Judgements: Eliciting Experts' Probabilities

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