In many systems, agents interact repeatedly with each other over an exogenously determined network and need to cooperate with each other by producing and sharing valuable knowledge or information with the agents with which they are connected. However, producing and sharing information can be costly for the agents themselves, while providing no direct immediate benefit to them. Hence, there are incentives for individual agents to shirk rather than to work - to free ride on the information production and sharing of other agents rather than to produce information themselves. In this paper, we develop a systematic framework for designing rating systems aimed at promoting efficient production and sharing in these networks, thereby significantly improving the social welfare (i.e., sum utility of agents) of such networks. The schemes proposed operated effectively even in settings where monitoring of agent behavior is subject to significant errors. In many scenarios our schemes achieve maximum social welfare; in others, we prove that optimal schemes necessarily fall short of maximum social welfare due to imperfect monitoring. The distinction between these scenarios arises from the tension between the social value of producing for others and the strategic value of withholding production. In some scenarios, the optimal scheme allows that less-productive agents shirk (not produce); this creates the largest incentives for more-productive agents to work at the socially-desired level. We establish conditions under which recommending 'work' to all agents is the optimal strategy and develop low-complexity algorithms to determine the optimal strategy in general settings for arbitrary information sharing networks.
- efficient shirking
- imperfect monitoring
- rating systems
- Repeated games
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Computer Networks and Communications