Present-biased optimization

This paper explores the behavior of present-biased agents, that is, agents who erroneously anticipate costs future actions compared to their real costs. Specifically, we extend original framework proposed by Akerlof (1991) for studying various aspects human related time-inconsistent planning, including procrastination, and abandonment, as well elegant graph-theoretic model encapsulating this recently Kleinberg Oren (2014). The benefit extension is twofold. First, it enables perform fine-grained analysis depending on optimization task they have perform. In particular, study covering tasks vs. hitting show ratio between cost solutions computed optimal may differ significantly problem constraints. Second, us not only underestimation costs, coupled with minimization problems, but also all combinations minimization/maximization, underestimation/overestimation. We four scenarios, establish upper bounds three them (the scenario was known be unbounded), providing a complete global picture far are concerned.