Playing the Wrong Game: Smoothness Bounds for Congestion Games with Behavioral Biases

摘要

In many situations a player may act so as to maximize a perceived utility that is not exactly her utility function, but rather some other, biased, utility. Examples of such biased utility functions are common in behavioral economics, and include risk attitudes, altruism, present-bias and so on. When analyzing a game, one may ask how inefficiency, measured by the Price of Anarchy (PoA) is affected by the perceived utilities. The smoothness method naturally extends to games with such perceived utilities or costs, regardless of the game or the behavioral bias. We show that such biased-smoothness is broadly applicable in the context of nonatomic congestion games. First, we show that on series-parallel networks we can use smoothness to yield PoA bounds even for diverse populations with different biases. Second, we identify various classes of cost functions and biases that are smooth, thereby substantially improving some recent results from the literature.