Human Adversaries in Opportunistic Crime Security Games : How Past success ( or failure ) affects future behavior

There are a growing number of automated decision aids based on game-theoretic algorithms in daily use by security agencies to assist in allocating or scheduling their limited security resources. These applications of game theory, based on the " security games " paradigm, are leading to fundamental research challenges: one major challenge is modeling human bounded rationality. More specifically, the security agency, assisted with an automated decision aid, is assumed to act with perfect rationality against a human adversary; it is important to investigate the bounded rationality of these human adversaries to improve effectiveness of security resource allocation. In (Abbasi et al, 2015), the authors provide an empirical investigation of adversary bounded rationality in opportunistic crime settings. In this paper, we propose two additional factors in the " subjective utility quantal response " model.