An agent-based concept to analyze elite-athletes' doping behavior

Abstract

A seemingly endless series of scandals has focused increasing public attention on the issue of doping among elite athletes. But we still do not know how many elite athletes really make use of banned drugs. In addition, we recognize the literature suffers a lack of appropriate game theory models for complex social interactions related to doping. Therefore, we think that an agent-based approach may allow doping behavior patterns in professional sports to be explored and elucidated. We conceptualize an agent-based model on three interacting objectives, namely (i) elite athletes, (ii) anti-doping laboratory and (iii) anti-doping agency. The latter agency announces antidoping rules and imposes penalties; the anti-doping laboratory executes doping controls and elite athletes compete for income. In particular, we focus on presenting an agent-based concept to analyze elite athletes' doping behavior. Using such an agentbased framework and computational simulations may lead in the future to policy recommendations for the fight against doping.