In communication systems where users share common resources, users' selfish
behavior usually results in suboptimal resource utilization. There have been
extensive works that model communication systems with selfish users as one-shot
games and propose incentive schemes to achieve Pareto optimal action profiles
as non-cooperative equilibria. However, in many communication systems, due to
strong negative externalities among users, the sets of feasible payoffs in
one-shot games are nonconvex.

This paper studies a class of incentive schemes based on intervention, where
there exists an intervention device that is able to monitor the actions of
users and to take an action that affects the payoffs of users. We consider the
case of perfect monitoring, where the intervention device can immediately
observe the actions of users without errors. We also assume that there exist
actions of the intervention device that are most and least preferred by all the
users and the intervention device, regardless of the actions of users.

User-generated content can be distributed at a low cost using peer-to-peer
(P2P) networks, but the free-rider problem hinders the utilization of P2P
networks. In order to achieve an efficient use of P2P networks, we investigate
fundamental issues on incentives in content production and sharing using game
theory. We build a basic model to analyze non-cooperative outcomes without an
incentive scheme and then use different game formulations derived from the
basic model to examine five incentive schemes: cooperative, payment, repeated
interaction, intervention, and enforced full sharing.