Adversarial risk analysis with incomplete information: a level-k approach.
This article proposes, develops, and illustrates the application of level-k game theory to adversarial risk analysis. Level-k reasoning, which assumes that players play strategically but have bounded rationality, is useful for operationalizing a Bayesian approach to adversarial risk analysis. It can be applied in a broad class of settings, including settings with asynchronous play and partial but incomplete revelation of early moves. Its computational and elicitation requirements are modest. We illustrate the approach with an application to a simple defend-attack model in which the defender's countermeasures are revealed with a probability less than one to the attacker before he decides on how or whether to attack.
Department of Economics, Wellesley College, 106 College Street, Wellesley, MA 02481, USA. crothsch@wellesley.edu
Casey
C
Rothschild
Laura
L
McLay
Seth
S
Guikema
D000465:Algorithms; D001499:Bayes Theorem; D005716:Game Theory; D006801:Humans; D018570:Risk Assessment / Q000379:methods*; D023481:Terrorism