title: Zero-Determinant Strategies in Iterated Public Goods Game.
abstract: Recently, Press and Dyson have proposed a new class of probabilistic and conditional strategies for the two-player iterated Prisoner's Dilemma, so-called zero-determinant strategies. A player adopting zero-determinant strategies is able to pin the expected payoff of the opponents or to enforce a linear relationship between his own payoff and the opponents' payoff, in a unilateral way. This paper considers zero-determinant strategies in the iterated public goods game, a representative multi-player game where in each round each player will choose whether or not to put his tokens into a public pot, and the tokens in this pot are multiplied by a factor larger than one and then evenly divided among all players. The analytical and numerical results exhibit a similar yet different scenario to the case of two-player games: (i) with small number of players or a small multiplication factor, a player is able to unilaterally pin the expected total payoff of all other players; (ii) a player is able to set the ratio between his payoff and the total payoff of all other players, but this ratio is limited by an upper bound if the multiplication factor exceeds a threshold that depends on the number of players.
authors: CompleX Lab, Web Sciences Center, University of Electronic Science and Technology of China, Chengdu 611731, China.
authors: Liming
authors: L
authors: Pan
authors: CompleX Lab, Web Sciences Center, University of Electronic Science and Technology of China, Chengdu 611731, China.
authors: Dong
authors: D
authors: Hao
authors: CompleX Lab, Web Sciences Center, University of Electronic Science and Technology of China, Chengdu 611731, China.
authors: Zhihai
authors: Z
authors: Rong
authors: CompleX Lab, Web Sciences Center, University of Electronic Science and Technology of China, Chengdu 611731, China.|Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China.
authors: Tao
authors: T
authors: Zhou
mesh_terms: D005716:Game Theory; D006801:Humans; D008962:Models, Theoretical