Adversarial Graph Traversal

TL;DR

This paper introduces an adversarial risk analysis framework for Bayesian agents navigating graphs with costs and payoffs, considering an opponent reducing payoffs, with applications in military, corporate, and game scenarios.

Contribution

It develops a novel approach combining Bayesian and adversarial analysis for route selection under strategic opposition.

Findings

Bayesian agents benefit from accurate cost/payoff distributions.

Prior knowledge of opponent strategies improves route planning.

Framework applicable to military, corporate, and strategic games.

Abstract

Suppose a Bayesian agent seeks to traverse a graph. Each time she crosses an edge, she pays a price. The first time she reaches a node, there is a payoff. She has an opponent who can reduce the payoffs. This paper uses adversarial risk analysis to find a solution to her route selection problem. It shows how the traveler is advantaged by having an accurate subjective distribution over the costs/payoffs and by having a Bayesian prior for her opponent's strategic choices. The results are relevant to military convoy routing, corporate competition, and certain games.