Altruism Design in Networked Public Goods Games

Abstract

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.