Many collective decision-making settings feature a strategic tension between
agents acting out of individual self-interest and promoting a common good.
These include wearing face masks during a pandemic, voting, and vaccination.
Networked public goods games capture this tension, with networks encoding
strategic interdependence among agents. Conventional models of public goods
games posit solely individual self-interest as a motivation, even though
altruistic motivations have long been known to play a significant role in
agents' decisions. We introduce a novel extension of public goods games to
account for altruistic motivations by adding a term in the utility function
that incorporates the perceived benefits an agent obtains from the welfare of
others, mediated by an altruism graph. Most importantly, we view altruism not
as immutable, but rather as a lever for promoting the common good. Our central
algorithmic question then revolves around the computational complexity of
modifying the altruism network to achieve desired public goods game investment
profiles. We first show that the problem can be solved using linear programming
when a principal can fractionally modify the altruism network. While the
problem becomes in general intractable if the principal's actions are
all-or-nothing, we exhibit several tractable special cases.

本论文介绍了一个扩展的公共物品博弈模型来考虑利他动机，其中将利他主义通过利他主义图中介的受益纳入效用函数，探索了调节共同利益的杠杆作用和计算复杂性。

网络公共物品博弈中的利他设计

Altruism Design in Networked Public Goods Games

Public goods games study the incentives of individuals to contribute to a
public good and their behaviors in equilibria. In this paper, we examine a
specific type of public goods game where players are networked and each has
binary actions, and focus on the algorithmic aspects of such games. First, we
show that checking the existence of a pure-strategy Nash equilibrium is
NP-complete. We then identify tractable instances based on restrictions of
either utility functions or of the underlying graphical structure. In certain
cases, we also show that we can efficiently compute a socially optimal Nash
equilibrium. Finally, we propose a heuristic approach for computing approximate
equilibria in general binary networked public goods games, and experimentally
demonstrate its effectiveness.

本文研究网络玩家的公共物品博弈，其中每个玩家具有二进制行动，并针对这类博弈的算法方面进行了研究，包括纯策略纳什均衡的存在性检测，限制条件下的可计算性以及启发式算法的提出与实验测试。