Understanding Police Force Resource Allocation using Adversarial Optimal Transport with Incomplete Information

2024/03/01 by Yinan Hu, Hu, Yinan, Juntao Chen +3
Business, Management and Accounting · Computer Science · Engineering · #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #FOS: Electrical engineering #Facility Location and Emergency Management #Military Defense Systems Analysis #Optimization and Search Problems #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2403.00972

openalex publication_date 2024/03/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Adversarial optimal transport has been proven useful as a mathematical formulation to model resource allocation problems to maximize the efficiency of transportation with an adversary, who modifies the data. It is often the case, however, that only the adversary knows which nodes are malicious and which are not. In this paper we formulate the problem of seeking adversarial optimal transport into Bayesian games. We construct the concept of Bayesian equilibrium and design a distributed algorithm that achieve those equilibria, making our model applicable to large-scale networks. Keywords: game theory, crime control, Markov games

Related

• Patrol Security Game: Defending Against Adversary with Freedom in Attack Timing, Location, and Duration
• Deceptive Path Planning: A Bayesian Game Approach
• Resilient and Distributed Discrete Optimal Transport with Deceptive Adversary: A Game-Theoretic Approach
• Solving a Stackelberg Game on Transportation Networks in a Dynamic Crime Scenario: A Mixed Approach on Multi-Layer Networks
• A Game-Theoretic Model and Best-Response Learning Method for Ad Hoc Coordination in Multiagent Systems